From f59a9bfd7b5f46a52dd7f55cd5977b42fa882a47 Mon Sep 17 00:00:00 2001 From: berges99 Date: Sat, 25 Jul 2026 12:32:46 +0200 Subject: [PATCH 01/30] feat(voice): add synthetic conversation replay harness Every voice test in python/tests/voice/ injects TranscriptEvents through a mock STT, which covers the session state machine and nothing below it: no audio, no real STT connection, no VAD, no endpointing. The bugs that reach production live in that gap. This replays ElevenLabs-synthesized speech into a real VoiceSession at real-time pace, acting as a fake browser across the three seams the session already exposes (paced audio in, event stream out, playback acks). No session changes were needed. 20 scenarios across support, food ordering, medical intake, banking and coding help. Expectations are declarative and compare normalized similarity, never verbatim transcripts, because STT wobbles between runs. Gating is delta-based against a committed baseline.json rather than absolute thresholds, which rot as providers drift. Scenarios that cannot pass today are marked known_failure with a written reason: they report but do not gate, and their desired expectations stay in the file instead of being rewritten to match broken behavior. Findings so far, all reproducible: - Trailing-modifier continuations are invisible to every detector. The fragment Flux commits mid-pause ("The pain started.") is a complete sentence in isolation and Namo scores it 1.00; only prosody marks the continuation, and SmartTurn v3 misses it too. - Flux's end_of_turn_confidence cannot fix that. Across 28 commits, fragments scored 0.690-0.920 and true turn ends 0.701-0.904. The best threshold catches 4 of 5 fragments while wrongly holding 35% of real turn ends. It measures whether speech stopped, not whether the thought finished. - lexical beats provider on Flux: 233ms vs 280ms median eou-to-audio and one fewer known failure, since support_pause merges correctly there instead of splitting and self-barging-in. - Reproduced a genuine ghost turn (a spurious single-token 'I' commit) and an intermittent split of short confirmations. Needs ELEVENLABS_API_KEY and DEEPGRAM_API_KEY, makes real network calls and runs in real time, so it is deliberately outside the default test path and unlike the rest of benchmarks/, which measures pure framework overhead. --- benchmarks/voice/.gitignore | 2 + benchmarks/voice/README.md | 241 +++++++++++++ benchmarks/voice/baseline.json | 84 +++++ benchmarks/voice/cli.py | 190 ++++++++++ benchmarks/voice/harness.py | 375 +++++++++++++++++++ benchmarks/voice/scenario.py | 642 +++++++++++++++++++++++++++++++++ benchmarks/voice/score.py | 300 +++++++++++++++ benchmarks/voice/synth.py | 210 +++++++++++ 8 files changed, 2044 insertions(+) create mode 100644 benchmarks/voice/.gitignore create mode 100644 benchmarks/voice/README.md create mode 100644 benchmarks/voice/baseline.json create mode 100644 benchmarks/voice/cli.py create mode 100644 benchmarks/voice/harness.py create mode 100644 benchmarks/voice/scenario.py create mode 100644 benchmarks/voice/score.py create mode 100644 benchmarks/voice/synth.py diff --git a/benchmarks/voice/.gitignore b/benchmarks/voice/.gitignore new file mode 100644 index 00000000..79ff55b8 --- /dev/null +++ b/benchmarks/voice/.gitignore @@ -0,0 +1,2 @@ +cache/ +results/ diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md new file mode 100644 index 00000000..69bf9c7a --- /dev/null +++ b/benchmarks/voice/README.md @@ -0,0 +1,241 @@ +# Voice replay harness + +Scripted conversations synthesized to audio with ElevenLabs and replayed into a +real `VoiceSession` at real-time pace, as if spoken into a mic. + +> **This directory breaks the rules of `benchmarks/`.** Everything else here +> measures pure framework overhead and needs no API keys. This is a *behavioral +> eval* of the voice stack: it needs `ELEVENLABS_API_KEY` and `DEEPGRAM_API_KEY`, +> it makes real network calls, and it runs in real time. Never wire it into the +> default test path. + +Full design: `planning/VOICE_REPLAY_HARNESS_PLAN.md`. + +## Why + +Every voice test in `python/tests/voice/` injects `TranscriptEvent`s through a +mock STT. That covers the session state machine and nothing below it — no audio, +no real STT connection, no VAD, no endpointing. The bugs that actually reach +production live in that gap. + +## Status: 20 scenarios across 5 domains, scoring and gating in place + +| File | Role | +|---|---| +| `synth.py` | ElevenLabs → cached PCM16 16k, plus PCM/frame/WAV helpers | +| `scenario.py` | script primitives, declarative expectations, scenario library | +| `harness.py` | fake browser: paced feeder, reactive driver, playback ack pump | +| `score.py` | JSONL records, scorecard aggregation, baseline diffing | +| `cli.py` | runner, reporting, regression gate | + +Still to come: the config matrix with parallelism, and AEC-leak simulation. + +## What it found + +**Trailing-modifier continuations are invisible to every detector we have.** When +the user pauses mid-thought, the fragment Flux commits is often a complete +sentence in isolation — "The pain started." before "maybe on Tuesday" — and Namo, +the text EOU that `--detector lexical` actually resolves to, scores it 1.00 +complete. That's a defensible text-only call: nothing in the words says a modifier +is coming. Only prosody does, and `--detector local` with SmartTurn v3 splits them +too. + +Text EOU handles *syntactic* incompleteness well ("I'd like to order a large" → +0.00 → held correctly) and *prosodic* continuation not at all. + +**Flux's `end_of_turn_confidence` does not rescue it.** The harness captured all +28 commits in a suite run: mid-thought fragments scored 0.690–0.920 and genuine +turn ends 0.701–0.904 — overlapping almost completely. The most confident +end-of-turn in the whole suite was a fragment mid-account-number (0.920). The best +threshold catches 4 of 5 fragments while wrongly holding 35% of real turn ends, +so it would add ~1.5s of dead air to a third of all turns. Flux's confidence +measures "has speech stopped", not "has the thought finished". Measured and +dropped rather than built. + +**`lexical` beats `provider` on correctness here, not just latency.** +`support_pause` merges into one clean turn under `lexical` and splits under +`provider`, where the second fragment barges in on the reply to the first. + +`banking_digits_pause` reproduces a genuine ghost turn — a spurious single-token +`'I'` commit. `banking_confirmation` intermittently splits "Yes, that's correct." +in two, again with a self-barge-in. + +All of these are recorded as known failures with written reasons, scoped to the +detectors where they actually occur, so they report on every run without blocking +the gate. + +Two cells are baselined so far: + +| cell | gated | p50 | p95 | n | known failures | +|---|---|---:|---:|---:|---:| +| `deepgram-flux/lexical` | 16/16 | 233ms | 297ms | 26 | 4 | +| `deepgram-flux/provider` | 13/13 | 280ms | 331ms | 28 | 5 | + +`lexical` is 47ms faster at the median *and* has one fewer known failure, which +suggests `provider` is the wrong default on Flux. Two cells is not a matrix +though — worth confirming across STT backends before changing anything. + +## Running + +```bash +export ELEVENLABS_API_KEY=... +export DEEPGRAM_API_KEY=... + +uv run python benchmarks/voice/cli.py # all scenarios +uv run python benchmarks/voice/cli.py --list # what exists +uv run python benchmarks/voice/cli.py -s barge_in -s pause # a subset +uv run python benchmarks/voice/cli.py --detector lexical # Timbal's HOLD path +uv run python benchmarks/voice/cli.py --stt elevenlabs +uv run python benchmarks/voice/cli.py --quick # ~30s subset, one per domain +uv run python benchmarks/voice/cli.py --repeat 3 # variance + flaky detection +uv run python benchmarks/voice/cli.py --quiet # results only +uv run python benchmarks/voice/cli.py --dump # WAVs to results/dumps/ +uv run python benchmarks/voice/cli.py --update-baseline # accept current behavior +``` + +Exit code is non-zero when any expectation fails or a regression is gated. + +## Results and the regression gate + +Every run appends one JSON line per scenario to `results/run-.jsonl`, +so a run stays analyzable after the fact rather than only pass/fail in the moment. + +Gating compares against `baseline.json` (committed — deliberately not under the +gitignored `results/`), one entry per `stt/detector` label so a single file covers +the whole matrix. It fails on **movement**, never on absolute thresholds, since +STT providers drift under us and yesterday's ceiling is tomorrow's false alarm: + +| Gated | Not gated | +|---|---| +| a scenario's pass rate drops | speedups | +| ghost turns increase | brand-new scenarios (nothing to compare) | +| median latency worsens >15% | latency with fewer than 20 samples | + +**Latency gates on p50, not p95.** With ~8 latency samples, p95 is the maximum in +disguise: one slow turn moved it 394ms → 477ms on an unchanged tree while all five +scenarios passed. The scorecard prints `n=` and says "ungated: too few samples" +outright, so nobody reads stability into a number that has none. + +Measured on this suite, p50 is worth gating and the tail is not — two independent +`--repeat 3` runs on an unchanged tree: + +| Statistic | Run A | Run B | Drift | +|---|---:|---:|---:| +| p50 | 298ms | 299ms | 0.3% | +| p95 | 383ms | 375ms | 2% | +| max | 462ms | 378ms | 18% | + +At 20 scenarios a single pass produces 28 latency samples, so `--repeat 1` clears +the floor on its own. Repeats still buy flaky detection: any scenario that passes +some repeats and fails others is reported by name as **FLAKY** — usually a real +race rather than a bad test. + +## Known failures + +A scenario can declare `known_failure={detector_or_star: reason}`. It still runs +and still reports, but it does not gate, and its *desired* expectations stay in +the file rather than being rewritten to match broken behavior. Known failures are +excluded from `per_scenario`, so marking one cannot quietly bake a defect into the +baseline. If one starts passing, that's reported as an unexpected pass telling you +to drop the marker — unless it's also `intermittent=True`, where passing sometimes +means nothing. + +`--update-baseline` refuses to save while any ungated run is failing. Otherwise +the first bad run silently becomes the accepted status quo. Fix it, or name it a +known failure with a written reason. + +Audio tooling, standalone: + +```bash +uv run python benchmarks/voice/synth.py "I'd like to order a large" # listen to a clip +uv run python benchmarks/voice/synth.py --verify # reproducibility check +``` + +## Writing a scenario + +A scenario is a script plus expectations. Silence is explicit and exact, because +gap duration is what turn detection actually keys on: + +```python +Scenario( + id="pause", + domain="food_ordering", + replies=["Sure — one large pepperoni. Anything else?"], + script=[ + Say("I'd like to order a large"), + Silence(1.6), + Say("pepperoni pizza please."), + Silence(3.0), + ], + expect=[Merged("I'd like to order a large pepperoni pizza please."), NoErrors()], +) +``` + +`AwaitAssistantAudio(offset_ms=600)` is the reactive step that makes barge-in +testable — the interruption lands at a known offset into the reply rather than +wherever a fixed sleep happens to fall. + +Expectations: `UserTurns`, `Merged`, `NoGhostTurns`, `Interrupted`, `HeardPrefix`, +`NoAgentReply`, `MaxLatency`, `NoErrors`. Text comparisons use normalized +similarity — **never assert verbatim transcripts**, STT wobbles between runs. + +## Per-detector expectations + +The same observable behavior can be correct for different reasons, so scenarios +can override expectations per detector (`expect_by_detector`) or declare which +detectors they're meaningful for at all (`detectors`). + +This matters: with `--stt deepgram-flux --detector provider`, Flux holds through +the `pause` scenario's 1.6s gap and merges inside its own turn machine, so that +run exercises none of Timbal's HOLD path. The same scenario under `--detector +lexical` does. `hesitation` is skipped entirely for `provider`, where trusting +the provider's commit means a bare "Um..." legitimately starts a turn. + +## What the current library measures + +`pause` (1.6s gap, merges) and `long_pause` (3.0s gap, splits) bracket Deepgram +Flux's turn window between those two durations. `barge_in` and `barge_in_late` +interrupt the same reply at 600ms and 2500ms, yielding heard prefixes of ~39 and +~77 characters — which is how you check the truncation path scales with real +playback position. + +## Voices + +Two distinct ElevenLabs voices — replaying the user in the assistant's voice +would trip the session's echo heuristics on legitimate speech. + +| Env var | Default | Role | +|---|---|---| +| `ELEVENLABS_VOICE_ID` | `1SM7GgM6IMuvQlz2BwM3` | assistant (TTS) | +| `TIMBAL_BENCH_USER_VOICE_ID` | `21m00Tcm4TlvDq8ikWAM` | user (replayed) | + +Both must exist on your account; cloned and custom voices are account-specific, +so override if the defaults 404. + +## Cache + +Synthesized clips land in `cache/`, keyed by a hash of +`(text, voice_id, tts_model)` — nothing is generated twice unless the script text +changes. Both `cache/` and `results/` are gitignored: audio does not belong in +git, and the generation script plus a content-addressed cache is reproducible +enough. + +## Reading the output + +Real-time pacing is mandatory, so a run takes as long as the conversation. + +``` +=== barge_in (deepgram-flux/provider) === + [+ 0.00s] session_started + [+ 0.00s] say "Tell me about your return policy." + [+ 1.63s] partial "Tell me about your return policy." + [+ 1.99s] await_audio 600ms into reply + [+ 2.46s] committed "Tell me about your return policy." + [+ 3.08s] metrics eou→audio 373.3ms segments 1 acks True vad_eou False + [+ 3.45s] say "Actually, cancel that." + [+ 4.92s] interrupted heard: 'Our return policy allows returns within' +``` + +`acks True` confirms the harness is exercising the client-truth playback path +rather than the wall-clock estimate fallback — production behavior, not a +degraded fallback. diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json new file mode 100644 index 00000000..cda18ac7 --- /dev/null +++ b/benchmarks/voice/baseline.json @@ -0,0 +1,84 @@ +{ + "deepgram-flux/lexical": { + "label": "deepgram-flux/lexical", + "stt": "deepgram-flux", + "detector": "lexical", + "runs": 16, + "passed": 16, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 233.2, + "latency_p95": 296.8, + "latency_min": 176.3, + "latency_max": 315.0, + "latency_samples": 26, + "per_scenario": { + "banking_digits": 1.0, + "banking_hesitation": 1.0, + "coding_barge_in": 1.0, + "coding_pause": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_pause": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_hesitation": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_late": 1.0, + "support_pause": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_digits_pause", + "food_list_pause", + "medical_hesitant_pause" + ], + "unexpected_passes": [], + "wall_secs": 136.0 + }, + "deepgram-flux/provider": { + "label": "deepgram-flux/provider", + "stt": "deepgram-flux", + "detector": "provider", + "runs": 13, + "passed": 13, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 280.0, + "latency_p95": 330.9, + "latency_min": 188.4, + "latency_max": 337.7, + "latency_samples": 28, + "per_scenario": { + "banking_digits": 1.0, + "coding_barge_in": 1.0, + "coding_pause": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_pause": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_late": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_digits_pause", + "food_list_pause", + "medical_hesitant_pause", + "support_pause" + ], + "unexpected_passes": [], + "wall_secs": 121.5 + } +} diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py new file mode 100644 index 00000000..c338ae89 --- /dev/null +++ b/benchmarks/voice/cli.py @@ -0,0 +1,190 @@ +"""Runner for the voice replay harness. + +Usage (from repo root):: + + export ELEVENLABS_API_KEY=... + export DEEPGRAM_API_KEY=... + + uv run python benchmarks/voice/cli.py # all scenarios + uv run python benchmarks/voice/cli.py -s barge_in -s pause # a subset + uv run python benchmarks/voice/cli.py --detector lexical # Timbal's HOLD path + uv run python benchmarks/voice/cli.py --repeat 3 # variance + flaky detection + uv run python benchmarks/voice/cli.py --update-baseline # accept current behavior + uv run python benchmarks/voice/cli.py --quiet # results only + uv run python benchmarks/voice/cli.py --dump # WAVs per run + +Replay runs in real time — the STT provider keeps its own wall clock and Silero +needs an unbroken stream — so a scenario costs roughly what the conversation +would cost a human. + +Exit code is non-zero when an expectation fails or a regression is gated. +""" + +from __future__ import annotations + +import argparse +import asyncio +import logging +import sys +import time + +import structlog +from dotenv import load_dotenv +from harness import HarnessConfig, RunResult, run_scenario +from scenario import SCENARIOS, select +from score import ( + build_scorecard, + compare, + format_scorecard, + load_baseline, + record, + save_baseline, + write_jsonl, +) +from synth import synthesize_clips + + +def _report(result: RunResult, known_failure: str | None, intermittent: bool = False) -> None: + print() + print(f" turns: {result.committed}") + if result.interrupted: + print(f" heard: {result.heard_text!r}") + if result.latencies_ms: + print(f" eou→audio: {', '.join(f'{v:.0f}ms' for v in result.latencies_ms)}") + print(f" audio: {result.audio_chunks} chunks, {result.audio_bytes} bytes") + print(f" wall: {result.wall_secs:.1f}s") + for failure in result.failures: + print(f" ✗ {failure}") + if known_failure and not result.passed: + print(f" KNOWN FAIL (not gated): {known_failure}") + elif known_failure and intermittent: + print(" PASS (known intermittent failure — passing proves nothing)") + elif known_failure: + print(" XPASS — known failure now passes, drop the known_failure marker") + else: + print(f" {'PASS' if result.passed else 'FAIL'}") + + +def _list_scenarios() -> int: + domain = "" + for s in SCENARIOS: + if s.domain != domain: + domain = s.domain + print(f"\n{domain}") + scope = "" if s.detectors is None else f" detectors={','.join(sorted(s.detectors))}" + print(f" {'*' if s.quick else ' '} {s.id:<24}{scope}") + for detector, reason in s.known_failure.items(): + kind = "intermittent" if s.intermittent else "known failure" + print(f" [{kind}, {detector}] {reason}") + if s.note: + print(f" {s.note}") + known = sum(1 for s in SCENARIOS if s.known_failure) + print(f"\n{len(SCENARIOS)} scenarios, {known} known failures; * = --quick subset") + return 0 + + +async def main() -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("-s", "--scenario", action="append", help="scenario id (repeatable)") + parser.add_argument("--stt", default="deepgram-flux", help="elevenlabs | deepgram-flux | deepgram-nova") + parser.add_argument("--detector", default="provider", help="heuristic | provider | lexical | local") + parser.add_argument("--language", default="en") + parser.add_argument("--repeat", type=int, default=1, help="runs per scenario (variance / flaky detection)") + parser.add_argument("--dump", action="store_true", help="write input/output WAVs per run") + parser.add_argument("--quick", action="store_true", help="representative subset (one per domain)") + parser.add_argument("--quiet", action="store_true", help="hide the per-event stream") + parser.add_argument("--list", action="store_true", help="list scenarios and exit") + parser.add_argument("--update-baseline", action="store_true", help="accept these results as the baseline") + parser.add_argument("--no-gate", action="store_true", help="report regressions without failing") + parser.add_argument("--verbose", action="store_true", help="keep timbal DEBUG logs") + args = parser.parse_args() + + if args.list: + return _list_scenarios() + + load_dotenv(override=True) + # Quiet by default because session/agent INFO logs bury the event stream; DEBUG + # under --verbose because that is where provider internals like Flux's + # end_of_turn_confidence are reported. + structlog.configure( + wrapper_class=structlog.make_filtering_bound_logger(logging.DEBUG if args.verbose else logging.WARNING) + ) + + config = HarnessConfig(stt=args.stt, detector=args.detector, language=args.language, dump=args.dump) + selected, skipped = select(args.scenario, config.detector, quick=args.quick) + if not selected: + print(f"nothing to run for detector={config.detector}; scenarios: {[s.id for s in SCENARIOS]}") + return 2 + + if args.update_baseline and (args.scenario or args.quick): + # A baseline entry is replaced wholesale, so accepting a filtered run would + # silently drop every scenario it didn't cover and disarm their gates. + print("refusing to update the baseline from a filtered run: it would drop the other scenarios") + return 2 + + clips = await synthesize_clips([text for s in selected for text in s.texts()]) + + records = [] + started = time.monotonic() + for repeat in range(max(1, args.repeat)): + for scenario in selected: + suffix = f" repeat {repeat + 1}/{args.repeat}" if args.repeat > 1 else "" + print(f"\n=== {scenario.id} ({config.label}){suffix} ===") + t0 = time.monotonic() + + def log(kind: str, detail: str = "", t0=t0) -> None: + if not args.quiet: + print(f" [+{time.monotonic() - t0:6.2f}s] {kind:<18}{detail}") + + result = await run_scenario(scenario, clips, config, log=log) + _report(result, scenario.known_failure_reason(config.detector), scenario.intermittent) + records.append(record(scenario, result, repeat=repeat)) + + for scenario in skipped: + print(f"\n=== {scenario.id} SKIPPED (not meaningful for {config.detector}) ===") + if scenario.note: + print(f" {scenario.note}") + + card = build_scorecard(records) + path = write_jsonl(records) + + print(f"\n{'─' * 72}") + print(format_scorecard(card)) + for name in card.known_failures: + reason = next(s.known_failure_reason(config.detector) for s in selected if s.id == name) + print(f" known: {name} — {reason}") + print(f" elapsed: {time.monotonic() - started:.0f}s results: {path}") + + if args.update_baseline: + if card.pass_rate < 1.0: + # Saving here would record the failure as the accepted status quo and + # disarm its gate. Either fix it, or mark it known_failure with a reason. + print( + "\n refusing to update the baseline: " + f"{card.runs - card.passed} run(s) failed and are not marked known_failure" + ) + return 1 + save_baseline(card) + print(f" baseline updated for {card.label}") + return 0 + + comparison = compare(card, load_baseline()) + if comparison.notes: + for line in comparison.notes: + print(f"\n note: {line}") + if comparison.improvements: + print("\n improvements vs baseline:") + for line in comparison.improvements: + print(f" + {line}") + if comparison.regressions: + print("\n REGRESSIONS vs baseline:") + for line in comparison.regressions: + print(f" - {line}") + + failed_expectations = card.pass_rate < 1.0 + gated = comparison.regressions and not args.no_gate + return 1 if (failed_expectations or gated) else 0 + + +if __name__ == "__main__": + sys.exit(asyncio.run(main())) diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py new file mode 100644 index 00000000..b2d15b70 --- /dev/null +++ b/benchmarks/voice/harness.py @@ -0,0 +1,375 @@ +"""Replay harness: drives a real ``VoiceSession`` from a scripted scenario. + +The harness is a **fake browser**. No session changes are needed because the +three seams already exist: + +=============== ========================================== ================== +Seam Session API Harness role +=============== ========================================== ================== +audio in ``session.run(audio_in)`` paced PCM feeder +events out yields ``VoiceSessionEvent`` script driver +playback ``session.playback.on_playback_ack(ms)`` ack pump +=============== ========================================== ================== + +The ack pump is not optional: without acks ``playback_acks_received`` is False +and interruption truncation runs on the wall-clock estimate, which is a +*different code path* than production. +""" + +from __future__ import annotations + +import asyncio +import time +from collections import deque +from collections.abc import AsyncIterator, Callable +from contextlib import aclosing +from dataclasses import dataclass, field + +from scenario import ( + AwaitAssistantAudio, + AwaitAssistantDone, + AwaitCommit, + Say, + Scenario, + Silence, +) +from synth import ( + ASSISTANT_VOICE_ID, + BYTES_PER_SECOND, + FRAME_SECS, + HERE, + SAMPLE_RATE, + SILENCE_FRAME, + TTS_MODEL, + frames, + write_wav, +) +from timbal import Agent +from timbal.core.test_model import TestModel +from timbal.state.tracing.providers import InMemoryTracingProvider +from timbal.voice import ( + AgentTextDone, + AudioInputConfig, + AudioOutput, + AudioOutputConfig, + SessionError, + SessionInterrupted, + SessionStarted, + TranscriptCommitted, + TranscriptPartial, + TurnMetrics, + TurnMetricsEvent, + VoiceSession, + VoiceSessionEvent, + resolve_stt, +) +from timbal.voice.elevenlabs import ElevenLabsStreamTTS + +DUMP_DIR = HERE / "results" / "dumps" + +Logger = Callable[[str, str], None] + + +@dataclass(frozen=True) +class HarnessConfig: + stt: str = "deepgram-flux" + detector: str = "provider" + language: str = "en" + dump: bool = False + + @property + def label(self) -> str: + return f"{self.stt}/{self.detector}" + + +@dataclass +class RunResult: + scenario_id: str + stt: str + detector: str + committed: list[str] = field(default_factory=list) + replies_spoken: list[str] = field(default_factory=list) + interrupted: bool = False + heard_text: str | None = None + latencies_ms: list[float] = field(default_factory=list) + metrics: list[TurnMetrics] = field(default_factory=list) + errors: list[str] = field(default_factory=list) + audio_chunks: int = 0 + audio_bytes: int = 0 + wall_secs: float = 0.0 + failures: list[str] = field(default_factory=list) + + @property + def passed(self) -> bool: + return not self.failures + + +# --------------------------------------------------------------------------- +# Fake browser internals +# --------------------------------------------------------------------------- + + +class PlaybackSim: + """Playhead over a gapless client-side queue, acked back at browser cadence. + + Caveat: this re-derives the same wall-clock schedule + ``BufferedPlaybackTracker`` computes internally, so it validates the *ack code + path* (``ack_received`` true, extrapolation branch live) rather than the + accuracy of the estimate. Real accuracy needs real playback hardware. + """ + + def __init__(self, bytes_per_second: int = BYTES_PER_SECOND) -> None: + self._bps = bytes_per_second + self._scheduled = 0 + self._playing_until = 0.0 + + def on_emit(self, num_bytes: int) -> None: + now = time.monotonic() + self._playing_until = max(now, self._playing_until) + num_bytes / self._bps + self._scheduled += num_bytes + + def on_interrupted(self) -> None: + self._scheduled = self.played_bytes + self._playing_until = time.monotonic() + + @property + def played_bytes(self) -> int: + remaining = max(0.0, self._playing_until - time.monotonic()) * self._bps + return max(0, int(self._scheduled - remaining)) + + @property + def played_ms(self) -> float: + return self.played_bytes / self._bps * 1000 + + +class ScriptFeeder: + """Paced PCM source: clip audio when speaking, silence the rest of the time.""" + + def __init__(self) -> None: + self._pending: deque[bytes] = deque() + self._stopped = False + + def push(self, pcm: bytes) -> None: + self._pending.extend(frames(pcm)) + + async def drain(self) -> None: + while self._pending: + await asyncio.sleep(FRAME_SECS) + + def stop(self) -> None: + self._stopped = True + + async def stream(self) -> AsyncIterator[bytes]: + """20ms frames, continuously. + + The stream never gaps: STT sockets and Silero cannot tell a pause in the + script from a stalled connection. Pacing follows an absolute schedule + because ``sleep(FRAME_SECS)`` per iteration accumulates drift and slowly + desynchronizes the replay from real time. + """ + next_at = time.monotonic() + while not self._stopped: + yield self._pending.popleft() if self._pending else SILENCE_FRAME + next_at += FRAME_SECS + await asyncio.sleep(max(0.0, next_at - time.monotonic())) + + +def stt_config(stt: str, language: str) -> AudioInputConfig: + if stt.startswith("deepgram"): + return AudioInputConfig(language=language, sample_rate=SAMPLE_RATE) + return AudioInputConfig( + model="scribe_v2_realtime", + language=language, + sample_rate=SAMPLE_RATE, + extra={ + "commit_strategy": "vad", + "min_speech_duration_ms": 100, + "vad_silence_threshold_secs": 1.2, + "vad_threshold": 0.4, + }, + ) + + +# --------------------------------------------------------------------------- +# Runner +# --------------------------------------------------------------------------- + + +async def run_scenario( + scenario: Scenario, + clips: dict[str, bytes], + config: HarnessConfig, + *, + log: Logger | None = None, +) -> RunResult: + """Replay one scenario against a live session and check its expectations.""" + result = RunResult(scenario_id=scenario.id, stt=config.stt, detector=config.detector) + + # Tracing must stay on: the session chains parent_id across turns for memory, + # and disabling it makes every turn after the first log "Parent trace not + # found". Pinned to in-memory so a platform config in the environment can't + # drag the bench into a real tracing backend. + agent = Agent( + name="bench", + model=TestModel(responses=scenario.replies), + tools=[], + tracing_provider=InMemoryTracingProvider, + ) + session = VoiceSession( + agent=agent, + stt=resolve_stt(config.stt), + tts=ElevenLabsStreamTTS(), + audio_input=stt_config(config.stt, config.language), + audio_output=AudioOutputConfig(model=TTS_MODEL, voice=ASSISTANT_VOICE_ID, sample_rate=SAMPLE_RATE), + turn_detector=config.detector, + record_audio=config.dump, + ) + + feeder = ScriptFeeder() + playback = PlaybackSim() + assistant_speaking = asyncio.Event() + # session.close() interrupts any reply still playing. That teardown interrupt + # is not a barge-in and must not be observed as one. + closing = asyncio.Event() + started = time.monotonic() + + def emit(kind: str, detail: str = "") -> None: + if log is not None: + log(kind, detail) + + async def ack_loop() -> None: + """Report the playhead the way the playground does — every 250ms.""" + while True: + await asyncio.sleep(0.25) + session.playback.on_playback_ack(playback.played_ms) + + async def wait_for(predicate, timeout: float, what: str) -> None: + deadline = time.monotonic() + timeout + while not predicate(): + if time.monotonic() > deadline: + result.errors.append(f"timed out waiting for {what}") + emit("timeout", what) + return + await asyncio.sleep(FRAME_SECS) + + async def drive() -> None: + # Baselines are taken when speech *starts*, not when the wait step is + # reached: a fast commit can land while the clip is still draining, and a + # wait armed after the fact would sit there until it timed out. + commits_at_say = 0 + replies_at_say = 0 + + for step in scenario.script: + if isinstance(step, Say): + emit("say", f'"{step.text}"') + commits_at_say = len(result.committed) + replies_at_say = len(result.replies_spoken) + feeder.push(clips[step.text]) + await feeder.drain() + elif isinstance(step, Silence): + emit("silence", f"{step.secs:.1f}s") + await asyncio.sleep(step.secs) + elif isinstance(step, AwaitAssistantAudio): + emit("await_audio", f"{step.offset_ms:.0f}ms into reply") + await wait_for(assistant_speaking.is_set, step.timeout, "assistant audio") + start = playback.played_ms + await wait_for( + lambda start=start, offset=step.offset_ms: playback.played_ms - start >= offset, + step.timeout, + f"{step.offset_ms:.0f}ms of playback", + ) + elif isinstance(step, AwaitCommit): + emit("await_commit") + await wait_for(lambda base=commits_at_say: len(result.committed) > base, step.timeout, "commit") + elif isinstance(step, AwaitAssistantDone): + emit("await_reply") + await wait_for(lambda base=replies_at_say: len(result.replies_spoken) > base, step.timeout, "reply") + await asyncio.sleep(0.5) # let trailing events land before teardown + closing.set() + feeder.stop() + await session.close() + + async with aclosing(session.run(feeder.stream())) as stream: + driver: asyncio.Task[None] | None = None + acker: asyncio.Task[None] | None = None + try: + async for event in stream: + _observe(event, result, playback, assistant_speaking, closing, emit) + if isinstance(event, SessionStarted): + started = time.monotonic() + acker = asyncio.create_task(ack_loop()) + driver = asyncio.create_task(drive()) + finally: + for task in (driver, acker): + if task is not None and not task.done(): + task.cancel() + for task in (driver, acker): + if task is not None: + await asyncio.gather(task, return_exceptions=True) + + result.wall_secs = time.monotonic() - started + + if config.dump: + for label, pcm in (("in", session.input_audio), ("out", session.output_audio)): + if pcm: + path = DUMP_DIR / f"{scenario.id}-{config.stt}-{config.detector}-{label}.wav" + write_wav(path, pcm) + emit("dump", str(path)) + + result.failures = [ + message + for expectation in scenario.expectations_for(config.detector) + if (message := expectation.check(result, scenario)) is not None + ] + return result + + +def _observe( + event: VoiceSessionEvent, + result: RunResult, + playback: PlaybackSim, + assistant_speaking: asyncio.Event, + closing: asyncio.Event, + emit: Logger, +) -> None: + if isinstance(event, AudioOutput): + # Individual chunks are far too chatty to log; the playhead is what matters. + playback.on_emit(len(event.data)) + assistant_speaking.set() + result.audio_chunks += 1 + result.audio_bytes += len(event.data) + elif isinstance(event, SessionStarted): + emit("session_started") + elif isinstance(event, TranscriptPartial): + emit("partial", f'"{event.text}"') + elif isinstance(event, TranscriptCommitted): + emit("committed", f'"{event.text}"{" (replace)" if event.replace else ""}') + if event.replace and result.committed: + result.committed[-1] = event.text + else: + result.committed.append(event.text) + elif isinstance(event, AgentTextDone): + emit("agent_done", f'"{event.text}"') + result.replies_spoken.append(event.text) + assistant_speaking.clear() + elif isinstance(event, SessionInterrupted): + playback.on_interrupted() + if closing.is_set(): + emit("teardown", "interrupt from close(), not counted") + else: + result.interrupted = True + result.heard_text = event.heard_text + emit("interrupted", f"heard: {event.heard_text!r}") + elif isinstance(event, TurnMetricsEvent): + metrics = event.metrics + result.metrics.append(metrics) + if metrics.eou_to_first_audio_ms is not None: + result.latencies_ms.append(metrics.eou_to_first_audio_ms) + emit( + "metrics", + f"eou→audio {metrics.eou_to_first_audio_ms}ms segments {metrics.tts_segments} " + f"acks {metrics.playback_acks_received} vad_eou {metrics.vad_endpointed}", + ) + elif isinstance(event, SessionError): + result.errors.append(event.message) + emit("error", event.message) diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py new file mode 100644 index 00000000..8c82cc3f --- /dev/null +++ b/benchmarks/voice/scenario.py @@ -0,0 +1,642 @@ +"""Scenario DSL for the voice replay harness. + +A scenario is a *script* (what the user does, including silences and reactive +barge-ins) plus *expectations* (behavioral labels checked after the run). + +Two rules learned the hard way, both encoded here: + +* **Silence is the real input.** Turn detection keys on gap duration, so every + pause is an explicit ``Silence`` with a duration we control rather than + something we hope the TTS produces. +* **Never assert verbatim transcripts.** STT wobbles between runs. Text + expectations compare normalized similarity against a threshold. +""" + +from __future__ import annotations + +import re +from dataclasses import dataclass, field +from difflib import SequenceMatcher +from typing import TYPE_CHECKING, Protocol + +if TYPE_CHECKING: + from harness import RunResult + + +# --------------------------------------------------------------------------- +# Script primitives +# --------------------------------------------------------------------------- + + +@dataclass(frozen=True) +class Say: + """Inject one synthesized clip.""" + + text: str + + +@dataclass(frozen=True) +class Silence: + """Inject exactly N seconds of silence.""" + + secs: float + + +@dataclass(frozen=True) +class AwaitAssistantAudio: + """Block until N ms of the assistant's reply has *played*, then continue. + + The seam that makes barge-in testable: the interruption lands at a known + offset into the reply instead of wherever a fixed sleep happens to fall. + """ + + offset_ms: float + timeout: float = 20.0 + + +@dataclass(frozen=True) +class AwaitCommit: + """Block until the session commits another user transcript.""" + + timeout: float = 15.0 + + +@dataclass(frozen=True) +class AwaitAssistantDone: + """Block until the agent finishes generating a reply.""" + + timeout: float = 20.0 + + +Step = Say | Silence | AwaitAssistantAudio | AwaitCommit | AwaitAssistantDone + + +# --------------------------------------------------------------------------- +# Text comparison +# --------------------------------------------------------------------------- + + +def normalize(text: str) -> str: + return re.sub(r"\s+", " ", re.sub(r"[^\w\s]", "", text.lower())).strip() + + +def similarity(a: str, b: str) -> float: + return SequenceMatcher(None, normalize(a), normalize(b)).ratio() + + +# --------------------------------------------------------------------------- +# Expectations +# --------------------------------------------------------------------------- + + +class Expectation(Protocol): + def check(self, result: RunResult, scenario: Scenario) -> str | None: + """Return ``None`` when satisfied, else a human-readable failure.""" + + +@dataclass(frozen=True) +class UserTurns: + """Exact number of committed user turns. + + The single most valuable assertion in the suite: a fragment wrongly split + into two turns, or two utterances wrongly merged into one, both show up here. + """ + + count: int + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + if len(result.committed) != self.count: + return f"expected {self.count} user turn(s), got {len(result.committed)}: {result.committed}" + return None + + +@dataclass(frozen=True) +class Merged: + """All spoken fragments arrived as one turn resembling ``text``.""" + + text: str + min_similarity: float = 0.85 + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + if len(result.committed) != 1: + return f"expected a single merged turn, got {len(result.committed)}: {result.committed}" + score = similarity(self.text, result.committed[0]) + if score < self.min_similarity: + return f"merged text similarity {score:.2f} < {self.min_similarity}: {result.committed[0]!r}" + return None + + +@dataclass(frozen=True) +class NoGhostTurns: + """Every committed turn resembles something the script actually said. + + Catches transcripts invented from echo, noise or a mis-fired watchdog. + """ + + min_similarity: float = 0.6 + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + spoken = [s.text for s in scenario.script if isinstance(s, Say)] + ghosts = [ + text + for text in result.committed + if not any(similarity(text, said) >= self.min_similarity for said in spoken) + ] + if ghosts: + return f"turns not present in the script: {ghosts}" + return None + + +@dataclass(frozen=True) +class Interrupted: + """Whether a barge-in cancelled the assistant. + + Teardown interrupts from ``session.close()`` are excluded by the harness, so + this only ever reflects a real barge-in. + """ + + expected: bool = True + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + if result.interrupted != self.expected: + return f"expected interrupted={self.expected}, got {result.interrupted}" + return None + + +@dataclass(frozen=True) +class HeardPrefix: + """``heard_text`` is a genuine prefix of the reply, optionally short enough. + + Guards the truncation path: memory and transcript must match what the user + actually heard, not the whole reply the agent generated. + """ + + max_chars: int | None = None + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + heard = result.heard_text + if not heard: + return f"expected heard text, got {heard!r}" + if not any(normalize(reply).startswith(normalize(heard)) for reply in scenario.replies): + return f"heard text is not a prefix of any reply: {heard!r}" + if self.max_chars is not None and len(heard) > self.max_chars: + return f"heard {len(heard)} chars > {self.max_chars}: {heard!r}" + return None + + +@dataclass(frozen=True) +class NoAgentReply: + """The agent never spoke — the utterance should not have started a turn.""" + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + if result.replies_spoken: + return f"expected no reply, agent said: {result.replies_spoken}" + return None + + +@dataclass(frozen=True) +class MaxLatency: + """Every turn's ``eou_to_first_audio_ms`` stayed under a ceiling.""" + + ms: float + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + over = [v for v in result.latencies_ms if v > self.ms] + if over: + return f"eou→audio over {self.ms}ms: {[round(v) for v in over]}" + return None + + +@dataclass(frozen=True) +class NoErrors: + def check(self, result: RunResult, scenario: Scenario) -> str | None: + if result.errors: + return f"session errors: {result.errors}" + return None + + +# --------------------------------------------------------------------------- +# Scenario +# --------------------------------------------------------------------------- + + +@dataclass(frozen=True) +class Scenario: + id: str + domain: str + replies: list[str] + """Fixed agent replies (``TestModel``). Reply *length* decides what a + barge-in can land inside, so these are part of the test, not scaffolding.""" + script: list[Step] + expect: list[Expectation] + expect_by_detector: dict[str, list[Expectation]] = field(default_factory=dict) + """Per-detector overrides. Necessary because the same observable behavior can + be correct for different reasons: Deepgram Flux merges a mid-thought pause + inside its own turn machine, while ``lexical`` merges it via Timbal's HOLD.""" + detectors: frozenset[str] | None = None + """Detectors this scenario is meaningful for (``None`` = all).""" + quick: bool = False + """Part of the representative ``--quick`` subset (one per domain, plus a barge-in).""" + known_failure: dict[str, str] = field(default_factory=dict) + """Detector (or ``"*"``) -> why this cannot pass today. + + The scenario still runs and still reports, but it does not gate, and its + *desired* expectations stay in the file rather than being rewritten to match + broken behavior. If it starts passing, that's reported as an unexpected pass. + """ + intermittent: bool = False + """The known failure is nondeterministic, so passing sometimes means nothing. + + Suppresses the unexpected-pass report, which would otherwise fire on roughly + half of all runs and train everyone to ignore it. + """ + note: str = "" + + def expectations_for(self, detector: str) -> list[Expectation]: + return self.expect_by_detector.get(detector, self.expect) + + def known_failure_reason(self, detector: str) -> str | None: + return self.known_failure.get(detector) or self.known_failure.get("*") + + def applies_to(self, detector: str) -> bool: + return self.detectors is None or detector in self.detectors + + def texts(self) -> list[str]: + return [s.text for s in self.script if isinstance(s, Say)] + + +# --------------------------------------------------------------------------- +# Library +# --------------------------------------------------------------------------- + +# Barge-in needs a reply long enough to interrupt *inside*, so reply length is +# part of the test rather than scaffolding. +_RETURN_POLICY_REPLY = ( + "Our return policy allows returns within thirty days of purchase, provided " + "the item is unused and you still have the original receipt or a valid proof " + "of purchase from one of our authorized retailers." +) +_MENU_REPLY = ( + "Today we have a roasted vegetable soup, a grilled chicken sandwich with " + "house slaw, a mushroom risotto, and for dessert a lemon tart or a chocolate " + "brownie served warm with vanilla ice cream." +) +_FEVER_REPLY = ( + "For a mild fever, rest and steady fluids are usually enough, and you can " + "take paracetamol to bring your temperature down, but if it stays above " + "thirty nine degrees for more than three days you should see a doctor." +) +_IMPORTS_REPLY = ( + "When Python imports a module it first checks the module cache in sys dot " + "modules, then searches each entry on the path in order, compiles the source " + "to bytecode, caches that bytecode on disk, and finally executes the module " + "body exactly once." +) + +# Bare fillers must not start a turn — except under `provider`, where trusting +# the provider's commit makes a commit the correct behavior. +_FILLER_DETECTORS = frozenset({"heuristic", "lexical", "local"}) +_FILLER_NOTE = "Skipped for `provider`: trusting the provider's commit means a bare filler legitimately starts a turn." + +# Measured, not assumed. The fragment Flux commits mid-pause is, in isolation, a +# grammatically complete sentence: "The pain started.", "I'll take a burger, some +# fries." Namo — the text EOU that `lexical` actually resolves to — scores both +# 1.00 complete, and scores them identically with and without the trailing period, +# so this is not an artifact of provider-added punctuation. Only prosody separates +# "The pain started [rising, continuing]" from "The pain started [falling, done]", +# and SmartTurn v3 under `--detector local` does not catch it either. The untapped +# signal is Flux's own `end_of_turn_confidence`, which Timbal currently logs and +# discards. +_TRAILING_MODIFIER_FAILURE = ( + "the committed fragment is a complete sentence in isolation, so text EOU scores it " + "complete; only prosody marks the continuation, and the audio EOU misses it too" +) + +# Under `provider` the session defers to the STT's endpointing entirely, so none of +# Timbal's hold logic runs and whatever Flux decides stands. +_PROVIDER_ENDPOINTING_FAILURE = ( + "`provider` defers to Flux's endpointing, which splits here; `lexical` merges it " + "correctly because Namo scores the fragment 0.00 incomplete" +) + +# Standard tail: wait for the turn to finish rather than sleeping a fixed guess, +# then leave a moment for any stray extra commit to show up. +_SETTLE = [AwaitCommit(), AwaitAssistantDone(), Silence(0.8)] + +SCENARIOS: list[Scenario] = [ + # -- support: long replies (barge-in surface), policy jargon --------------- + Scenario( + id="support_simple", + domain="support", + replies=["Returns are accepted within thirty days of purchase."], + script=[Say("What's your return policy?"), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + quick=True, + ), + Scenario( + id="support_pause", + domain="support", + replies=["I can help with that. Do you have the order number?"], + script=[ + Say("I want to return an item I bought"), + Silence(1.5), + Say("about three weeks ago."), + *_SETTLE, + ], + expect=[ + Merged("I want to return an item I bought about three weeks ago."), + NoGhostTurns(), + Interrupted(False), + NoErrors(), + ], + known_failure={"provider": _PROVIDER_ENDPOINTING_FAILURE}, + note=( + "The one scenario where a detector choice changes correctness rather than " + "latency: under `provider` it splits and the second fragment barges in on the " + "reply to the first, under `lexical` it merges into a single clean turn." + ), + ), + Scenario( + id="support_barge_in", + domain="support", + replies=[_RETURN_POLICY_REPLY], + script=[ + Say("Tell me about your return policy."), + AwaitAssistantAudio(offset_ms=600), + Say("Actually, cancel that."), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), HeardPrefix(max_chars=80), NoGhostTurns(), NoErrors()], + quick=True, + ), + Scenario( + id="support_barge_in_late", + domain="support", + replies=[_RETURN_POLICY_REPLY], + script=[ + Say("Tell me about your return policy."), + AwaitAssistantAudio(offset_ms=2500), + Say("Okay, thanks."), + *_SETTLE, + ], + expect=[ + UserTurns(2), + Interrupted(True), + HeardPrefix(), # later barge-in -> longer prefix, so no ceiling + NoGhostTurns(), + NoErrors(), + ], + note="Pairs with support_barge_in: same reply, later offset, measurably longer heard text.", + ), + # -- food_ordering: enumerations, mid-list pauses -------------------------- + Scenario( + id="food_simple", + domain="food_ordering", + replies=["One large coffee and a croissant. Anything else?"], + script=[Say("Can I get a large coffee and a croissant?"), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + ), + Scenario( + id="food_pause", + domain="food_ordering", + replies=["Sure — one large pepperoni. Anything else?"], + script=[ + Say("I'd like to order a large"), + Silence(1.5), + Say("pepperoni pizza please."), + *_SETTLE, + ], + expect=[ + Merged("I'd like to order a large pepperoni pizza please."), + NoGhostTurns(), + Interrupted(False), + NoErrors(), + ], + quick=True, + note=( + "Under deepgram-flux + provider, Flux holds through the gap and merges inside " + "its own turn machine — no Timbal HOLD involved. Under lexical it is our HOLD. " + "Same expectation, different mechanism." + ), + ), + Scenario( + id="food_long_pause", + domain="food_ordering", + replies=["Got it — a large pepperoni pizza."], + script=[ + Say("I'd like to order a large"), + Silence(3.0), # long enough that a split is the correct answer + Say("pepperoni pizza please."), + *_SETTLE, + ], + expect=[UserTurns(2), NoGhostTurns(), NoErrors()], + expect_by_detector={ + # Observed, with the mechanism deliberately not asserted: under `lexical` + # this merges, and the event trace shows Flux never committing the first + # fragment at all — it streams partials through the whole 3s gap and emits + # one commit. So the merge happens inside Flux, not in Timbal's HOLD. + # Why the same cached audio splits under `provider` is still unexplained; + # `commit()` is a no-op for Flux, so it is not an obvious forced endpoint. + "lexical": [ + Merged("I'd like to order a large pepperoni pizza please."), + NoGhostTurns(), + NoErrors(), + ], + }, + note=( + "Splits under `provider`, merges under `lexical`, from byte-identical cached " + "audio. Consistent across runs but not yet explained — see the comment above." + ), + ), + Scenario( + id="food_list_pause", + domain="food_ordering", + replies=["A burger, fries and a chocolate milkshake. Coming up."], + script=[ + Say("I'll take a burger, some fries,"), + Silence(1.4), # mid-list breath, not an end of turn + Say("and a chocolate milkshake."), + *_SETTLE, + ], + expect=[ + Merged("I'll take a burger, some fries, and a chocolate milkshake."), + NoGhostTurns(), + NoErrors(), + ], + known_failure={"*": _TRAILING_MODIFIER_FAILURE}, + note="A pause after a comma mid-enumeration: prosody says continue even though the gap is long.", + ), + Scenario( + id="food_barge_in", + domain="food_ordering", + replies=[_MENU_REPLY], + script=[ + Say("Tell me what's on the menu today."), + AwaitAssistantAudio(offset_ms=800), + Say("Just the specials, please."), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), HeardPrefix(), NoGhostTurns(), NoErrors()], + ), + # -- medical_intake: hesitation-heavy ------------------------------------- + Scenario( + id="medical_simple", + domain="medical_intake", + replies=["How long has the headache lasted?"], + script=[Say("I've had a headache since yesterday."), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + ), + Scenario( + id="medical_hesitation", + domain="medical_intake", + replies=["Take your time."], + script=[Say("Um..."), Silence(2.5)], + expect=[NoAgentReply(), NoErrors()], + detectors=_FILLER_DETECTORS, + quick=True, + note=_FILLER_NOTE, + ), + Scenario( + id="medical_hesitant_pause", + domain="medical_intake", + replies=["Thanks. Has it changed since then?"], + script=[ + Say("The pain started"), + Silence(1.5), + Say("maybe on Tuesday."), + *_SETTLE, + ], + expect=[Merged("The pain started maybe on Tuesday."), NoGhostTurns(), NoErrors()], + known_failure={"*": _TRAILING_MODIFIER_FAILURE}, + note="Trailing off mid-recall, the archetypal case for holding instead of endpointing.", + ), + Scenario( + id="medical_barge_in", + domain="medical_intake", + replies=[_FEVER_REPLY], + script=[ + Say("What should I do about a fever?"), + AwaitAssistantAudio(offset_ms=700), + Say("Sorry, one more thing."), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), HeardPrefix(), NoGhostTurns(), NoErrors()], + ), + # -- banking: digit strings and short confirmations ------------------------ + Scenario( + id="banking_digits", + domain="banking", + replies=["Thank you. I've found the account."], + # Spelled out, because that is what comes back: ElevenLabs speaks "447291" + # digit by digit and Deepgram transcribes the words, so a numeral here would + # look like a hallucinated turn to every text comparison. + script=[Say("My account number is four four seven two nine one."), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + note="Digit strings are the STT-hostile case: no lexical context to fall back on.", + ), + Scenario( + id="banking_digits_pause", + domain="banking", + replies=["Got it, account 447291."], + script=[ + Say("My account number is four four seven"), + Silence(1.4), + Say("two nine one."), + *_SETTLE, + ], + expect=[ + Merged("My account number is four four seven two nine one.", min_similarity=0.75), + NoGhostTurns(min_similarity=0.4), + NoErrors(), + ], + known_failure={"*": "splits into three turns, one of them a spurious single-token commit (observed: 'I')"}, + note=( + "The hardest merge in the suite: a digit string broken across a pause, with no " + "words to hint continuation. Also the only scenario so far to produce a genuine " + "ghost turn, which is worth keeping precisely because it reproduces one." + ), + ), + Scenario( + id="banking_confirmation", + domain="banking", + replies=["Great, the transfer is scheduled."], + script=[Say("Yes, that's correct."), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + quick=True, + known_failure={ + "*": "intermittently splits into 'Yes.' + \"That's correct.\", and the second " + "fragment barges in on the reply to the first" + }, + intermittent=True, + note=( + "Observed passing and failing on consecutive runs of an unchanged tree. Short " + 'utterances have a history here: ElevenLabs once transcribed "yes." / "work." ' + "as partials that never committed at all, hanging the session." + ), + ), + Scenario( + id="banking_hesitation", + domain="banking", + replies=["No problem, take your time."], + script=[Say("Uh..."), Silence(2.5)], + expect=[NoAgentReply(), NoErrors()], + detectors=_FILLER_DETECTORS, + note=_FILLER_NOTE, + ), + # -- coding_help: technical tokens --------------------------------------- + Scenario( + id="coding_simple", + domain="coding_help", + replies=["It means you indexed something that doesn't support indexing."], + script=[Say("What does TypeError not subscriptable mean?"), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(min_similarity=0.5), Interrupted(False), NoErrors()], + quick=True, + note="Technical tokens have no conversational prior, so STT leans harder on acoustics.", + ), + Scenario( + id="coding_pause", + domain="coding_help", + replies=["Can you paste the traceback?"], + script=[ + Say("I'm getting an error in my"), + Silence(1.5), + Say("async generator function."), + *_SETTLE, + ], + expect=[ + Merged("I'm getting an error in my async generator function.", min_similarity=0.8), + NoGhostTurns(min_similarity=0.5), + NoErrors(), + ], + ), + Scenario( + id="coding_barge_in", + domain="coding_help", + replies=[_IMPORTS_REPLY], + script=[ + Say("Explain how Python handles imports."), + AwaitAssistantAudio(offset_ms=900), + Say("Actually, never mind."), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), HeardPrefix(), NoGhostTurns(), NoErrors()], + ), +] + + +def select( + ids: list[str] | None, + detector: str, + *, + quick: bool = False, +) -> tuple[list[Scenario], list[Scenario]]: + """Return ``(applicable, skipped)`` for a detector, filtered by ids or ``quick``.""" + chosen = SCENARIOS + if ids: + chosen = [s for s in chosen if s.id in set(ids)] + if quick: + chosen = [s for s in chosen if s.quick] + return ( + [s for s in chosen if s.applies_to(detector)], + [s for s in chosen if not s.applies_to(detector)], + ) diff --git a/benchmarks/voice/score.py b/benchmarks/voice/score.py new file mode 100644 index 00000000..089a940d --- /dev/null +++ b/benchmarks/voice/score.py @@ -0,0 +1,300 @@ +"""Scoring, result persistence and regression gating for the voice replay harness. + +Three ideas do the work here: + +* **Records, not assertions.** Every run serializes to one JSONL line, so a run + is analyzable after the fact rather than only pass/fail at the time. +* **Deltas, not absolutes.** Gating compares against a committed baseline. + Absolute thresholds rot within a week because STT providers drift under us — + yesterday's 400ms ceiling is tomorrow's false alarm in both directions. +* **Flaky is a finding, not noise.** STT is nondeterministic, so a scenario that + passes some repeats and fails others is surfaced by name. Those are usually a + real race, not a bad test. +""" + +from __future__ import annotations + +import json +import time +from dataclasses import asdict, dataclass, field +from pathlib import Path + +from harness import RunResult +from scenario import Scenario, similarity + +HERE = Path(__file__).parent +RESULTS_DIR = HERE / "results" +# Not under results/ (which is gitignored) — the baseline is meant to be committed. +BASELINE_PATH = HERE / "baseline.json" + +# Gate thresholds. Deliberately loose: this catches direction changes, not noise. +LATENCY_REGRESSION_RATIO = 1.15 +# Latency gating needs a distribution, not a handful of samples. At suite sizes +# below this, p95 is effectively the maximum and a single slow turn trips the +# gate while every scenario passes (observed: 394ms -> 477ms on an unchanged +# tree). Below the floor, latency is reported but never gated, and the gate uses +# p50 — robust to one outlier — rather than p95. +MIN_LATENCY_SAMPLES = 20 + + +# --------------------------------------------------------------------------- +# Records +# --------------------------------------------------------------------------- + + +@dataclass +class RunRecord: + """One scenario × config × repeat.""" + + scenario: str + domain: str + stt: str + detector: str + repeat: int + passed: bool + failures: list[str] + user_turns: int + ghost_turns: int + interrupted: bool + heard_chars: int | None + latencies_ms: list[float] + vad_endpointed: list[bool] + errors: list[str] + wall_secs: float + known_failure: str = "" + """Non-empty when this scenario is expected to fail for this detector.""" + intermittent: bool = False + + @property + def xfail(self) -> bool: + return bool(self.known_failure) + + @property + def xpass(self) -> bool: + return self.xfail and self.passed and not self.intermittent + + def to_json(self) -> str: + return json.dumps(asdict(self)) + + +def count_ghost_turns(result: RunResult, scenario: Scenario, min_similarity: float = 0.6) -> int: + """Committed turns that resemble nothing the script said. + + Tracked as a metric independent of whether a scenario declared the matching + expectation — a hallucinated transcript is worth knowing about everywhere. + """ + spoken = scenario.texts() + return sum(1 for text in result.committed if not any(similarity(text, said) >= min_similarity for said in spoken)) + + +def record(scenario: Scenario, result: RunResult, repeat: int = 0) -> RunRecord: + return RunRecord( + scenario=scenario.id, + domain=scenario.domain, + stt=result.stt, + detector=result.detector, + repeat=repeat, + passed=result.passed, + failures=list(result.failures), + user_turns=len(result.committed), + ghost_turns=count_ghost_turns(result, scenario), + interrupted=result.interrupted, + heard_chars=None if result.heard_text is None else len(result.heard_text), + latencies_ms=[round(v, 1) for v in result.latencies_ms], + vad_endpointed=[m.vad_endpointed for m in result.metrics], + errors=list(result.errors), + wall_secs=round(result.wall_secs, 2), + known_failure=scenario.known_failure_reason(result.detector) or "", + intermittent=scenario.intermittent, + ) + + +def write_jsonl(records: list[RunRecord], path: Path | None = None) -> Path: + path = path or RESULTS_DIR / f"run-{time.strftime('%Y%m%d-%H%M%S')}.jsonl" + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text("".join(f"{r.to_json()}\n" for r in records)) + return path + + +# --------------------------------------------------------------------------- +# Aggregation +# --------------------------------------------------------------------------- + + +def percentile(values: list[float], q: float) -> float | None: + """Linear-interpolated percentile. ``q`` in [0, 1]. + + Rounded: these land in a committed baseline, and float noise like + ``382.97999999999996`` makes review diffs unreadable. + """ + if not values: + return None + ordered = sorted(values) + if len(ordered) == 1: + return round(ordered[0], 1) + pos = q * (len(ordered) - 1) + low = int(pos) + high = min(low + 1, len(ordered) - 1) + return round(ordered[low] + (ordered[high] - ordered[low]) * (pos - low), 1) + + +@dataclass +class Scorecard: + label: str + stt: str + detector: str + runs: int + """Gated runs only — known failures are counted separately.""" + passed: int + pass_rate: float + ghost_turns: int + errors: int + latency_p50: float | None + latency_p95: float | None + latency_min: float | None = None + latency_max: float | None = None + latency_samples: int = 0 + per_scenario: dict[str, float] = field(default_factory=dict) + """Gated scenario id -> pass rate across repeats. Known failures are excluded, so + marking one cannot quietly bake broken behavior into the baseline.""" + flaky: list[str] = field(default_factory=list) + known_failures: list[str] = field(default_factory=list) + unexpected_passes: list[str] = field(default_factory=list) + wall_secs: float = 0.0 + + +def build_scorecard(records: list[RunRecord]) -> Scorecard: + if not records: + raise ValueError("no records to score") + + gated = [r for r in records if not r.xfail] + by_scenario: dict[str, list[RunRecord]] = {} + for r in gated: + by_scenario.setdefault(r.scenario, []).append(r) + + per_scenario = {name: sum(r.passed for r in runs) / len(runs) for name, runs in by_scenario.items()} + # Latency describes the stack, not an expectation, so known failures still count. + latencies = [v for r in records for v in r.latencies_ms] + passed = sum(r.passed for r in gated) + + return Scorecard( + label=f"{records[0].stt}/{records[0].detector}", + stt=records[0].stt, + detector=records[0].detector, + runs=len(gated), + passed=passed, + pass_rate=passed / len(gated) if gated else 1.0, + ghost_turns=sum(r.ghost_turns for r in gated), + errors=sum(len(r.errors) for r in gated), + latency_p50=percentile(latencies, 0.5), + latency_p95=percentile(latencies, 0.95), + latency_min=min(latencies) if latencies else None, + latency_max=max(latencies) if latencies else None, + latency_samples=len(latencies), + per_scenario=dict(sorted(per_scenario.items())), + flaky=sorted(name for name, rate in per_scenario.items() if 0.0 < rate < 1.0), + known_failures=sorted({r.scenario for r in records if r.xfail}), + unexpected_passes=sorted({r.scenario for r in records if r.xpass}), + wall_secs=round(sum(r.wall_secs for r in records), 1), + ) + + +def format_scorecard(card: Scorecard) -> str: + lines = [ + f"{card.label}: {card.passed}/{card.runs} passed ({card.pass_rate:.0%})", + f" ghost turns: {card.ghost_turns} session errors: {card.errors}", + ] + if card.latency_p50 is not None: + gated = "" if card.latency_samples >= MIN_LATENCY_SAMPLES else " (ungated: too few samples)" + lines.append( + f" eou→audio: p50 {card.latency_p50:.0f}ms p95 {card.latency_p95:.0f}ms " + f"range {card.latency_min:.0f}-{card.latency_max:.0f}ms " + f"n={card.latency_samples}{gated}" + ) + failing = [name for name, rate in card.per_scenario.items() if rate < 1.0] + if failing: + lines.append(f" failing: {', '.join(failing)}") + if card.flaky: + lines.append(f" FLAKY: {', '.join(card.flaky)} (passed some repeats, not others)") + if card.known_failures: + lines.append(f" known fail: {', '.join(card.known_failures)} (reported, not gated)") + if card.unexpected_passes: + lines.append( + f" XPASS: {', '.join(card.unexpected_passes)} — now passing, drop the known_failure marker" + ) + return "\n".join(lines) + + +# --------------------------------------------------------------------------- +# Baseline + gating +# --------------------------------------------------------------------------- + + +def load_baseline(path: Path = BASELINE_PATH) -> dict[str, dict]: + if not path.exists(): + return {} + return json.loads(path.read_text()) + + +def save_baseline(card: Scorecard, path: Path = BASELINE_PATH) -> None: + """Merge one config's scorecard into the baseline, leaving the others alone.""" + baseline = load_baseline(path) + baseline[card.label] = asdict(card) + path.write_text(json.dumps(dict(sorted(baseline.items())), indent=2) + "\n") + + +@dataclass +class Comparison: + regressions: list[str] = field(default_factory=list) + improvements: list[str] = field(default_factory=list) + notes: list[str] = field(default_factory=list) + """Informational: movement seen but deliberately not gated.""" + + @property + def ok(self) -> bool: + return not self.regressions + + +def compare(card: Scorecard, baseline: dict[str, dict]) -> Comparison: + """Gate on movement away from the baseline, not on absolute thresholds.""" + out = Comparison() + previous = baseline.get(card.label) + if previous is None: + out.notes.append(f"no baseline for {card.label} yet — run with --update-baseline") + return out + + was: dict[str, float] = previous.get("per_scenario", {}) + for name, rate in card.per_scenario.items(): + before = was.get(name) + if before is None: + continue + if rate < before: + out.regressions.append(f"{name}: pass rate {before:.0%} → {rate:.0%}") + elif rate > before: + out.improvements.append(f"{name}: pass rate {before:.0%} → {rate:.0%}") + + new_scenarios = sorted(set(card.per_scenario) - set(was)) + if new_scenarios: + out.notes.append(f"new scenarios, nothing to compare: {', '.join(new_scenarios)}") + + for name in card.unexpected_passes: + out.improvements.append(f"{name}: known failure now passes — drop the known_failure marker") + + if card.ghost_turns > previous.get("ghost_turns", 0): + out.regressions.append(f"ghost turns {previous.get('ghost_turns', 0)} → {card.ghost_turns}") + + before_p50 = previous.get("latency_p50") + if before_p50 and card.latency_p50: + moved = card.latency_p50 / before_p50 + delta = f"eou→audio p50 {before_p50:.0f}ms → {card.latency_p50:.0f}ms" + enough = min(card.latency_samples, previous.get("latency_samples", 0)) >= MIN_LATENCY_SAMPLES + if moved > LATENCY_REGRESSION_RATIO: + worse = f"{delta} (>{(LATENCY_REGRESSION_RATIO - 1) * 100:.0f}% worse)" + if enough: + out.regressions.append(worse) + else: + out.notes.append(f"{worse} — not gated, fewer than {MIN_LATENCY_SAMPLES} samples") + elif moved < 1 / LATENCY_REGRESSION_RATIO: + out.improvements.append(delta) + + return out diff --git a/benchmarks/voice/synth.py b/benchmarks/voice/synth.py new file mode 100644 index 00000000..a031fe55 --- /dev/null +++ b/benchmarks/voice/synth.py @@ -0,0 +1,210 @@ +"""Audio synthesis, caching and PCM helpers for the voice replay harness. + +ElevenLabs -> raw PCM16 16k mono, cached by a hash of ``(text, voice, model)``. +Synthesis is the only expensive part of the harness, so nothing is ever generated +twice for unchanged script text. + +Everything here is deterministic once the cache is warm: the same script always +composes to the same bytes, which is what makes replay runs comparable. + +Standalone use — hear what the harness will actually feed the session:: + + uv run python benchmarks/voice/synth.py "I'd like to order a large" + uv run python benchmarks/voice/synth.py --verify +""" + +from __future__ import annotations + +import argparse +import asyncio +import hashlib +import logging +import os +import sys +import wave +from collections.abc import Iterable, Iterator +from pathlib import Path + +import structlog +from dotenv import load_dotenv +from timbal.voice import AudioOutputConfig +from timbal.voice.elevenlabs import ElevenLabsStreamTTS + +SAMPLE_RATE = 16_000 +BYTES_PER_SECOND = SAMPLE_RATE * 2 # PCM16 mono +FRAME_SECS = 0.02 +FRAME_BYTES = int(BYTES_PER_SECOND * FRAME_SECS) +SILENCE_FRAME = b"\x00" * FRAME_BYTES + +TTS_MODEL = os.environ.get("TIMBAL_TTS_MODEL", "eleven_flash_v2_5") +# Distinct voices for the two sides: replaying the user in the assistant's voice +# would trip the session's echo heuristics on legitimate speech. +ASSISTANT_VOICE_ID = os.environ.get("ELEVENLABS_VOICE_ID", "1SM7GgM6IMuvQlz2BwM3") +USER_VOICE_ID = os.environ.get("TIMBAL_BENCH_USER_VOICE_ID", "21m00Tcm4TlvDq8ikWAM") + +HERE = Path(__file__).parent +CACHE_DIR = HERE / "cache" + + +# --------------------------------------------------------------------------- +# PCM helpers +# --------------------------------------------------------------------------- + + +def silence(secs: float) -> bytes: + """Exactly ``secs`` of silence, rounded to whole 20ms frames.""" + return SILENCE_FRAME * max(0, round(secs / FRAME_SECS)) + + +def duration_secs(pcm: bytes) -> float: + return len(pcm) / BYTES_PER_SECOND + + +def frame_pad(pcm: bytes) -> bytes: + """Zero-pad to a whole number of frames. + + Clips rarely end on a frame boundary. Padding each part keeps the composed + stream frame-aligned at the cost of <20ms of silence at a seam, which is + below anything turn detection can resolve. + """ + remainder = len(pcm) % FRAME_BYTES + return pcm if remainder == 0 else pcm + b"\x00" * (FRAME_BYTES - remainder) + + +def frames(pcm: bytes) -> Iterator[bytes]: + """Split into 20ms frames, padding the tail.""" + padded = frame_pad(pcm) + for i in range(0, len(padded), FRAME_BYTES): + yield padded[i : i + FRAME_BYTES] + + +def compose(parts: Iterable[bytes | float]) -> bytes: + """Concatenate clips (``bytes``) and silences (``float`` seconds). + + The static half of a script: everything except reactive steps, which need the + session's own audio timing and therefore live in the harness. + """ + return b"".join(frame_pad(p) if isinstance(p, bytes) else silence(p) for p in parts) + + +def write_wav(path: Path, pcm: bytes) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + with wave.open(str(path), "wb") as wav: + wav.setnchannels(1) + wav.setsampwidth(2) + wav.setframerate(SAMPLE_RATE) + wav.writeframes(pcm) + + +# --------------------------------------------------------------------------- +# Synthesis + cache +# --------------------------------------------------------------------------- + + +def clip_path(text: str, voice_id: str = USER_VOICE_ID, model: str = TTS_MODEL) -> Path: + digest = hashlib.sha256(f"{model}|{voice_id}|{text}".encode()).hexdigest()[:16] + return CACHE_DIR / f"{digest}.pcm" + + +async def synthesize_clips( + texts: Iterable[str], + *, + voice_id: str = USER_VOICE_ID, + model: str = TTS_MODEL, + quiet: bool = False, +) -> dict[str, bytes]: + """Return ``{text: pcm}``, synthesizing only what the cache is missing.""" + wanted = list(dict.fromkeys(texts)) + CACHE_DIR.mkdir(parents=True, exist_ok=True) + missing = [t for t in wanted if not clip_path(t, voice_id, model).exists()] + + if missing: + if not quiet: + print(f"synthesizing {len(missing)} clip(s) with voice {voice_id}...") + tts = ElevenLabsStreamTTS() + await tts.connect(AudioOutputConfig(model=model, voice=voice_id, sample_rate=SAMPLE_RATE)) + try: + for text in missing: + buf = bytearray() + async for chunk in tts.synthesize(text): + buf.extend(chunk) + if not buf: + raise RuntimeError(f"ElevenLabs returned no audio for {text!r}") + clip_path(text, voice_id, model).write_bytes(bytes(buf)) + finally: + await tts.close() + + return {t: clip_path(t, voice_id, model).read_bytes() for t in wanted} + + +# --------------------------------------------------------------------------- +# CLI +# --------------------------------------------------------------------------- + +_VERIFY_PARTS: list[str | float] = [ + "Verification clip one.", + 0.5, + "Verification clip two.", +] + + +async def _verify() -> int: + """Phase 1 exit criterion: clips and silences compose byte-exactly.""" + texts = [p for p in _VERIFY_PARTS if isinstance(p, str)] + checks: list[tuple[str, bool, str]] = [] + + first = await synthesize_clips(texts) + second = await synthesize_clips(texts) # must be a pure cache read + checks.append(("cache read is stable", first == second, f"{len(first)} clip(s)")) + + def _build(clips: dict[str, bytes]) -> bytes: + return compose([clips[p] if isinstance(p, str) else p for p in _VERIFY_PARTS]) + + a, b = _build(first), _build(second) + digest = hashlib.sha256(a).hexdigest()[:16] + checks.append(("compose is byte-exact", a == b, f"sha256:{digest}")) + checks.append(("frame-aligned", len(a) % FRAME_BYTES == 0, f"{len(a)} bytes")) + checks.append(("non-empty", duration_secs(a) > 1.0, f"{duration_secs(a):.2f}s")) + + gap = silence(0.5) + checks.append(("silence is exact", duration_secs(gap) == 0.5, f"{len(gap)} bytes")) + checks.append(("frames round-trip", b"".join(frames(a)) == a, f"{len(a) // FRAME_BYTES} frames")) + + for name, ok, detail in checks: + print(f" {'ok ' if ok else 'FAIL'} {name:<24} {detail}") + failed = [name for name, ok, _ in checks if not ok] + print(f"\n{len(checks) - len(failed)}/{len(checks)} checks passed") + return 0 if not failed else 1 + + +async def main() -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("text", nargs="*", help="text to synthesize") + parser.add_argument("-o", "--out", type=Path, help="write a WAV here (default: results/synth/)") + parser.add_argument("--voice", default=USER_VOICE_ID) + parser.add_argument("--model", default=TTS_MODEL) + parser.add_argument("--verify", action="store_true", help="check byte-exact reproducibility") + parser.add_argument("--verbose", action="store_true", help="keep timbal debug logs") + args = parser.parse_args() + + load_dotenv(override=True) + if not args.verbose: + structlog.configure(wrapper_class=structlog.make_filtering_bound_logger(logging.WARNING)) + + if args.verify: + return await _verify() + if not args.text: + parser.print_help() + return 2 + + text = " ".join(args.text) + clips = await synthesize_clips([text], voice_id=args.voice, model=args.model) + pcm = clips[text] + out = args.out or HERE / "results" / "synth" / f"{clip_path(text, args.voice, args.model).stem}.wav" + write_wav(out, pcm) + print(f"{duration_secs(pcm):.2f}s {len(pcm)} bytes -> {out}") + return 0 + + +if __name__ == "__main__": + sys.exit(asyncio.run(main())) From f75476842ba128e29645d8998593446064d4ed00 Mon Sep 17 00:00:00 2001 From: berges99 Date: Sat, 25 Jul 2026 15:48:00 +0200 Subject: [PATCH 02/30] fix(voice): synthesize fluent utterances whole, slice at timestamps MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The replay harness synthesized every Say() on its own, so ElevenLabs rendered each mid-sentence fragment as a complete sentence and gave it a falling, finished contour. A speaker who pauses mid-sentence does not. Measured with Smart Turn v3 on identical words ending at the same boundary, "I want to return an item I bought" scores 0.986 (finished) standalone and 0.019 (mid-thought) cut from the fluent render — a swing of 0.967 from intonation alone. The pause scenarios were testing TTS phrasing rather than turn-taking. fluent() now renders such sentences in one TTS call and slices them at the character timestamps ElevenLabs returns with the audio. Three known failures disappeared outright on every detector — food_list_pause, support_pause, banking_digits_pause — and their markers are deleted rather than relaxed. Also adds support_closer, the only scenario covering what the text-complete hold tier protects, after nearly removing that tier on evidence that turned out to be blind: disabling it merges medical_hesitant_pause 5/5 with no suite regression, but costs 2.7s of dead air on an under-scored closer (speech end to reply 0.91s -> 3.59s). Behavior left alone. No product code changes. Two candidate fixes were measured and rejected: restricting the effective_text_eou punctuation rescue to interrogatives is a one-for-one wash, and gating the hold-shrink on a confidently-wrong audio score was fitted to the old fixture — on faithful audio a real fragment scores 0.054, below the closer it was meant to separate from. All three cells re-baselined at 100%: local 19/19, lexical 19/19, provider 16/16. Known failures 6 -> 3. --- benchmarks/voice/README.md | 150 +++++++++++++++++++--------- benchmarks/voice/baseline.json | 91 ++++++++++++----- benchmarks/voice/cli.py | 5 +- benchmarks/voice/harness.py | 2 +- benchmarks/voice/scenario.py | 172 +++++++++++++++++++++++---------- benchmarks/voice/synth.py | 135 +++++++++++++++++++++++++- 6 files changed, 432 insertions(+), 123 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 69bf9c7a..365017f6 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -18,11 +18,11 @@ mock STT. That covers the session state machine and nothing below it — no audi no real STT connection, no VAD, no endpointing. The bugs that actually reach production live in that gap. -## Status: 20 scenarios across 5 domains, scoring and gating in place +## Status: 21 scenarios across 5 domains, scoring and gating in place | File | Role | |---|---| -| `synth.py` | ElevenLabs → cached PCM16 16k, plus PCM/frame/WAV helpers | +| `synth.py` | ElevenLabs → cached PCM16 16k, fluent-utterance slicing, PCM/frame/WAV helpers | | `scenario.py` | script primitives, declarative expectations, scenario library | | `harness.py` | fake browser: paced feeder, reactive driver, playback ack pump | | `score.py` | JSONL records, scorecard aggregation, baseline diffing | @@ -32,48 +32,98 @@ Still to come: the config matrix with parallelism, and AEC-leak simulation. ## What it found -**Trailing-modifier continuations are invisible to every detector we have.** When -the user pauses mid-thought, the fragment Flux commits is often a complete -sentence in isolation — "The pain started." before "maybe on Tuesday" — and Namo, -the text EOU that `--detector lexical` actually resolves to, scores it 1.00 -complete. That's a defensible text-only call: nothing in the words says a modifier -is coming. Only prosody does, and `--detector local` with SmartTurn v3 splits them -too. - -Text EOU handles *syntactic* incompleteness well ("I'd like to order a large" → -0.00 → held correctly) and *prosodic* continuation not at all. - -**Flux's `end_of_turn_confidence` does not rescue it.** The harness captured all -28 commits in a suite run: mid-thought fragments scored 0.690–0.920 and genuine -turn ends 0.701–0.904 — overlapping almost completely. The most confident -end-of-turn in the whole suite was a fragment mid-account-number (0.920). The best -threshold catches 4 of 5 fragments while wrongly holding 35% of real turn ends, -so it would add ~1.5s of dead air to a third of all turns. Flux's confidence -measures "has speech stopped", not "has the thought finished". Measured and -dropped rather than built. - -**`lexical` beats `provider` on correctness here, not just latency.** -`support_pause` merges into one clean turn under `lexical` and splits under -`provider`, where the second fragment barges in on the reply to the first. - -`banking_digits_pause` reproduces a genuine ghost turn — a spurious single-token -`'I'` commit. `banking_confirmation` intermittently splits "Yes, that's correct." -in two, again with a self-barge-in. - -All of these are recorded as known failures with written reasons, scoped to the -detectors where they actually occur, so they report on every run without blocking -the gate. - -Two cells are baselined so far: - -| cell | gated | p50 | p95 | n | known failures | -|---|---|---:|---:|---:|---:| -| `deepgram-flux/lexical` | 16/16 | 233ms | 297ms | 26 | 4 | -| `deepgram-flux/provider` | 13/13 | 280ms | 331ms | 28 | 5 | - -`lexical` is 47ms faster at the median *and* has one fewer known failure, which -suggests `provider` is the wrong default on Flux. Two cells is not a matrix -though — worth confirming across STT backends before changing anything. +**The biggest thing it found was a bug in the harness, not in Timbal.** +Synthesizing each `Say()` on its own gives every fragment sentence-final +intonation, because ElevenLabs renders a fragment as a complete sentence. A +speaker who pauses mid-sentence does no such thing. Measured with Smart Turn v3 on +identical words ending at the same boundary, "I want to return an item I bought" +scores **0.986 (finished)** rendered standalone and **0.019 (mid-thought)** cut out +of the fluent whole-sentence render — a swing of 0.967 from intonation alone. + +Three of the known failures were that artifact. `fluent()` now renders such +sentences in one TTS call and slices them at the character timestamps ElevenLabs +returns alongside the audio; `food_list_pause`, `support_pause` and +`banking_digits_pause` went green across every detector, and median latency +improved ~10% because turns stopped being split and re-run. + +The lesson generalizes beyond this harness: a synthetic voice fixture tests TTS +phrasing unless you deliberately build it to test turn-taking. Anything previously +concluded about prosody from per-fragment audio is worth re-checking. + +**It also invalidated a fix that had looked good.** Before fluent synthesis, +`local` failed `medical_hesitant_pause` because Smart Turn scored the fragment +0.395 — correctly mid-thought — armed a HOLD, and a text-confidence tier then cut +that hold from 3.0s to 0.35s against a 1.5s pause, because Flux's auto-appended +period made the transcript read finished. Gating the shrink on a *confidently* +wrong audio score fixed it and held 3/3: under-scored closers sat near the floor +("That's all." → 0.115) and real fragments just under the threshold. On faithful +audio that same fragment scores **0.054** — below the closer — so the bands invert +and the threshold turns out to have been fitting the artifact. Reverted rather +than shipped. + +**Trailing-modifier continuations are still unsolved, but only one case is left, +and it is a genuine tradeoff rather than a bug.** `medical_hesitant_pause` splits +on every detector. Namo scores "The pain started" 1.00 complete with or without the +trailing period, so this was never about provider-added punctuation; the audio EOU +hears the continuation clearly (0.054) but the text-complete tier cuts its hold to +0.35s, under the 1.5s pause. `local` merges it about one run in five. + +Disabling that tier makes it merge 5/5 with no other scenario regressing — but the +suite had nothing covering what the tier protects, so that result was measured +blind. `support_closer` now covers it: Smart Turn under-scores "That's all." at +0.115 while the text reads finished, and removing the tier costs **2.7s of dead +air** there (speech end to reply: 0.91s with the tier, 3.59s without). Thirteen of +fourteen closers measured score above 0.5 and never reach the tier at all, so the +population it protects is small — but 2.7s is far too expensive to trade for the +fragment case, so the shipped behavior stands. + +Gating the tier on the audio score does not resolve it either. At the tier, closers +score {0.115} and fragments {0.054, 0.376}: the fragments straddle the closer, so +no threshold separates them. + +**Careful with `eou→audio`: it is measured from the *accepted* commit, so it does +not include hold time.** A detector that holds for three seconds and then answers +in 200ms reports 200ms. Cross-detector latency comparisons in this README are only +meaningful where holds do not fire; where they do, read the event timeline instead. + +**Flux's `end_of_turn_confidence` does not rescue it.** Across all 28 commits in a +suite run, mid-thought fragments scored 0.690–0.920 and genuine turn ends +0.701–0.904 — overlapping almost completely, and the most confident "end of turn" +in the suite was a fragment mid-account-number. The best available threshold +catches 4 of 5 fragments while wrongly holding 35% of real turn ends, roughly +1.5s of dead air on a third of all turns. It measures "has speech stopped", not +"has the thought finished". Measured and dropped rather than built. + +**The punctuation rescue in `effective_text_eou` is load-bearing in both +directions.** It promotes a Namo-incomplete verdict whenever the text ends in +terminal punctuation, which wrongly rescues `support_pause`'s fragment (Namo 0.00, +correct) and rightly rescues "Pepperoni pizza, please." (Namo 0.00, wrong). +Restricting it to question marks fixes the first and breaks the second, one for +one — both are Namo 0.00 plus a provider-added period, so nothing separates them. +Left alone. + +`banking_confirmation` intermittently splits "Yes, that's correct." in two with a +self-barge-in, and `banking_digits_pause` under `provider` still emits the one +genuine ghost turn the suite reproduces. Both are recorded as known failures with +written reasons, scoped to the detectors where they actually occur, so they report +on every run without blocking the gate. + +Three cells are baselined so far: + +| cell | gated | p50 | p95 | known failures | +|---|---|---:|---:|---:| +| `deepgram-flux/local` | 19/19 | 228ms | 300ms | 2 | +| `deepgram-flux/lexical` | 19/19 | 230ms | 301ms | 2 | +| `deepgram-flux/provider` | 16/16 | 222ms | 326ms | 3 | + +The three are indistinguishable at the median now. `provider` carries the extra +known failure — it is the only configuration that still splits a digit string +across a pause and emits the one ghost turn the suite reproduces — and it has the +longest tail, so it still looks like the wrong default on Flux. `local` and +`lexical` are otherwise equivalent here, which means the audio EOU is not currently +buying anything Namo does not already provide, at least on Flux with clean audio. +Three cells is not a matrix; worth confirming across STT backends before changing +any default. ## Running @@ -162,15 +212,21 @@ Scenario( domain="food_ordering", replies=["Sure — one large pepperoni. Anything else?"], script=[ - Say("I'd like to order a large"), - Silence(1.6), - Say("pepperoni pizza please."), + *fluent("I'd like to order a large", 1.6, "pepperoni pizza please."), Silence(3.0), ], expect=[Merged("I'd like to order a large pepperoni pizza please."), NoErrors()], ) ``` +**Use `fluent()` for any pause *inside* a sentence.** It renders the whole sentence +in one TTS call and slices it at character timestamps, so each fragment keeps the +intonation it actually has mid-sentence. Writing that example as three separate +steps — `Say(...)`, `Silence(1.6)`, `Say(...)` — is the trap described above: it +hands the detector a fragment that sounds finished and tests TTS phrasing instead +of turn-taking. Plain `Say` is for genuinely separate utterances, like the second +half of a barge-in. + `AwaitAssistantAudio(offset_ms=600)` is the reactive step that makes barge-in testable — the interruption lands at a known offset into the reply rather than wherever a fixed sleep happens to fall. diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index cda18ac7..88bf6761 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -3,23 +3,25 @@ "label": "deepgram-flux/lexical", "stt": "deepgram-flux", "detector": "lexical", - "runs": 16, - "passed": 16, + "runs": 19, + "passed": 19, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 233.2, - "latency_p95": 296.8, - "latency_min": 176.3, - "latency_max": 315.0, - "latency_samples": 26, + "latency_p50": 229.9, + "latency_p95": 301.2, + "latency_min": 184.6, + "latency_max": 373.8, + "latency_samples": 25, "per_scenario": { "banking_digits": 1.0, + "banking_digits_pause": 1.0, "banking_hesitation": 1.0, "coding_barge_in": 1.0, "coding_pause": 1.0, "coding_simple": 1.0, "food_barge_in": 1.0, + "food_list_pause": 1.0, "food_long_pause": 1.0, "food_pause": 1.0, "food_simple": 1.0, @@ -28,39 +30,82 @@ "medical_simple": 1.0, "support_barge_in": 1.0, "support_barge_in_late": 1.0, + "support_closer": 1.0, + "support_pause": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "medical_hesitant_pause" + ], + "unexpected_passes": [], + "wall_secs": 135.3 + }, + "deepgram-flux/local": { + "label": "deepgram-flux/local", + "stt": "deepgram-flux", + "detector": "local", + "runs": 19, + "passed": 19, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 227.8, + "latency_p95": 299.8, + "latency_min": 185.0, + "latency_max": 308.9, + "latency_samples": 25, + "per_scenario": { + "banking_digits": 1.0, + "banking_digits_pause": 1.0, + "banking_hesitation": 1.0, + "coding_barge_in": 1.0, + "coding_pause": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_list_pause": 1.0, + "food_long_pause": 1.0, + "food_pause": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_hesitation": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_late": 1.0, + "support_closer": 1.0, "support_pause": 1.0, "support_simple": 1.0 }, "flaky": [], "known_failures": [ "banking_confirmation", - "banking_digits_pause", - "food_list_pause", "medical_hesitant_pause" ], "unexpected_passes": [], - "wall_secs": 136.0 + "wall_secs": 132.6 }, "deepgram-flux/provider": { "label": "deepgram-flux/provider", "stt": "deepgram-flux", "detector": "provider", - "runs": 13, - "passed": 13, + "runs": 16, + "passed": 16, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 280.0, - "latency_p95": 330.9, - "latency_min": 188.4, - "latency_max": 337.7, - "latency_samples": 28, + "latency_p50": 222.1, + "latency_p95": 326.4, + "latency_min": 187.3, + "latency_max": 357.2, + "latency_samples": 27, "per_scenario": { "banking_digits": 1.0, "coding_barge_in": 1.0, "coding_pause": 1.0, "coding_simple": 1.0, "food_barge_in": 1.0, + "food_list_pause": 1.0, "food_long_pause": 1.0, "food_pause": 1.0, "food_simple": 1.0, @@ -68,17 +113,19 @@ "medical_simple": 1.0, "support_barge_in": 1.0, "support_barge_in_late": 1.0, + "support_closer": 1.0, + "support_pause": 1.0, "support_simple": 1.0 }, "flaky": [], "known_failures": [ "banking_confirmation", "banking_digits_pause", - "food_list_pause", - "medical_hesitant_pause", - "support_pause" + "medical_hesitant_pause" ], - "unexpected_passes": [], - "wall_secs": 121.5 + "unexpected_passes": [ + "banking_digits_pause" + ], + "wall_secs": 118.8 } } diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index c338ae89..af467600 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -41,7 +41,7 @@ save_baseline, write_jsonl, ) -from synth import synthesize_clips +from synth import synthesize_clips, synthesize_fluent def _report(result: RunResult, known_failure: str | None, intermittent: bool = False) -> None: @@ -122,7 +122,8 @@ async def main() -> int: print("refusing to update the baseline from a filtered run: it would drop the other scenarios") return 2 - clips = await synthesize_clips([text for s in selected for text in s.texts()]) + clips = await synthesize_clips([text for s in selected for text in s.standalone_texts()]) + clips |= await synthesize_fluent([g for s in selected for g in s.fluent_groups()]) records = [] started = time.monotonic() diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index b2d15b70..08b0cc1a 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -264,7 +264,7 @@ async def drive() -> None: emit("say", f'"{step.text}"') commits_at_say = len(result.committed) replies_at_say = len(result.replies_spoken) - feeder.push(clips[step.text]) + feeder.push(clips[step.clip_key]) await feeder.drain() elif isinstance(step, Silence): emit("silence", f"{step.secs:.1f}s") diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 8c82cc3f..49b7791c 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -30,9 +30,19 @@ @dataclass(frozen=True) class Say: - """Inject one synthesized clip.""" + """Inject one synthesized clip. + + ``utterance`` marks this as slice ``part`` of a longer sentence rendered in + one piece — see :func:`fluent`. + """ text: str + utterance: str | None = None + part: int = 0 + + @property + def clip_key(self) -> str: + return self.text if self.utterance is None else f"{self.utterance}#{self.part}" @dataclass(frozen=True) @@ -71,6 +81,34 @@ class AwaitAssistantDone: Step = Say | Silence | AwaitAssistantAudio | AwaitCommit | AwaitAssistantDone +def fluent(*parts: str | float) -> list[Step]: + """Script one sentence the speaker pauses inside, keeping mid-sentence prosody. + + Takes alternating text and gap seconds — ``fluent("The pain started", 1.5, + "maybe on Tuesday.")`` — and renders the joined sentence in a single TTS call, + slicing it at the character timestamps. + + Synthesizing the fragments separately is what a naive harness does, and it is + wrong in a way that silently changes the answer: ElevenLabs renders each + fragment as its own sentence with a falling contour. Measured with Smart Turn + v3 on identical words, "I want to return an item I bought" scores 0.986 + (finished) standalone and 0.019 (mid-thought) cut from the fluent render. Use + this for any pause *inside* a sentence; use bare ``Say`` for genuinely separate + utterances. + """ + texts = [p for p in parts if isinstance(p, str)] + utterance = " ".join(texts) + steps: list[Step] = [] + index = 0 + for part in parts: + if isinstance(part, str): + steps.append(Say(part, utterance=utterance, part=index)) + index += 1 + else: + steps.append(Silence(part)) + return steps + + # --------------------------------------------------------------------------- # Text comparison # --------------------------------------------------------------------------- @@ -136,7 +174,7 @@ class NoGhostTurns: min_similarity: float = 0.6 def check(self, result: RunResult, scenario: Scenario) -> str | None: - spoken = [s.text for s in scenario.script if isinstance(s, Say)] + spoken = scenario.texts() ghosts = [ text for text in result.committed @@ -262,8 +300,21 @@ def applies_to(self, detector: str) -> bool: return self.detectors is None or detector in self.detectors def texts(self) -> list[str]: + """Everything the user says, fluent parts included — what was *spoken*.""" return [s.text for s in self.script if isinstance(s, Say)] + def standalone_texts(self) -> list[str]: + """Clips synthesized on their own; fluent parts are sliced from one render.""" + return [s.text for s in self.script if isinstance(s, Say) and s.utterance is None] + + def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: + """``(whole utterance, parts)`` for each sentence spoken across pauses.""" + groups: dict[str, list[str]] = {} + for step in self.script: + if isinstance(step, Say) and step.utterance is not None: + groups.setdefault(step.utterance, []).append(step.text) + return [(utterance, tuple(parts)) for utterance, parts in groups.items()] + # --------------------------------------------------------------------------- # Library @@ -299,17 +350,22 @@ def texts(self) -> list[str]: _FILLER_NOTE = "Skipped for `provider`: trusting the provider's commit means a bare filler legitimately starts a turn." # Measured, not assumed. The fragment Flux commits mid-pause is, in isolation, a -# grammatically complete sentence: "The pain started.", "I'll take a burger, some -# fries." Namo — the text EOU that `lexical` actually resolves to — scores both -# 1.00 complete, and scores them identically with and without the trailing period, -# so this is not an artifact of provider-added punctuation. Only prosody separates -# "The pain started [rising, continuing]" from "The pain started [falling, done]", -# and SmartTurn v3 under `--detector local` does not catch it either. The untapped -# signal is Flux's own `end_of_turn_confidence`, which Timbal currently logs and -# discards. +# grammatically complete sentence — "The pain started." before "maybe on Tuesday" — +# and Namo, the text EOU that `lexical` resolves to, scores it 1.00 complete with or +# without the trailing period. Only prosody marks the continuation, and while the +# audio EOU does hear it (Smart Turn scores this fragment 0.054 on fluent audio), a +# text-confidence tier shrinks the resulting hold to 0.35s against a 1.5s pause, so +# `local` splits it too — intermittently; it merges roughly one run in five. Flux's +# own `end_of_turn_confidence` is no help either: sampled across the suite, +# fragments (0.690-0.920) and true ends (0.701-0.904) overlap almost entirely. +# +# Every other scenario in this class stopped failing once fluent synthesis landed +# (see `fluent`), which is the measure of how much the old per-`Say` fixture was +# testing TTS phrasing rather than turn-taking. _TRAILING_MODIFIER_FAILURE = ( "the committed fragment is a complete sentence in isolation, so text EOU scores it " - "complete; only prosody marks the continuation, and the audio EOU misses it too" + "complete; the audio EOU does hear the continuation but the text-complete tier cuts " + "its hold to 0.35s" ) # Under `provider` the session defers to the STT's endpointing entirely, so none of @@ -338,9 +394,7 @@ def texts(self) -> list[str]: domain="support", replies=["I can help with that. Do you have the order number?"], script=[ - Say("I want to return an item I bought"), - Silence(1.5), - Say("about three weeks ago."), + *fluent("I want to return an item I bought", 1.5, "about three weeks ago."), *_SETTLE, ], expect=[ @@ -349,11 +403,27 @@ def texts(self) -> list[str]: Interrupted(False), NoErrors(), ], - known_failure={"provider": _PROVIDER_ENDPOINTING_FAILURE}, note=( - "The one scenario where a detector choice changes correctness rather than " - "latency: under `provider` it splits and the second fragment barges in on the " - "reply to the first, under `lexical` it merges into a single clean turn." + "Used to split under `provider` and `local` and was marked a known failure for " + "both. Fluent synthesis fixed it outright: rendered standalone this fragment " + "scores 0.986 finished, and cut from the whole sentence it scores 0.019." + ), + ), + Scenario( + id="support_closer", + domain="support", + replies=["Happy to help. Have a good day."], + script=[Say("That's all."), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + note=( + "The case the text-complete hold tier exists for, and the only one in the suite: " + "Smart Turn under-scores this closer (0.115 — 13 of 14 closers measured score " + "above 0.5 and never reach the tier) while the text reads finished, so the hold " + "is armed on an utterance that is actually over. Disabling the tier costs 2.7s of " + "dead air here (speech end to reply: 0.91s with it, 3.59s without), which is why " + "the tier survives even though it is what splits medical_hesitant_pause. " + "Deliberately carries no MaxLatency: eou→audio is measured from the *accepted* " + "commit, so it reads ~200ms either way and cannot see the hold." ), ), Scenario( @@ -401,9 +471,7 @@ def texts(self) -> list[str]: domain="food_ordering", replies=["Sure — one large pepperoni. Anything else?"], script=[ - Say("I'd like to order a large"), - Silence(1.5), - Say("pepperoni pizza please."), + *fluent("I'd like to order a large", 1.5, "pepperoni pizza please."), *_SETTLE, ], expect=[ @@ -424,28 +492,28 @@ def texts(self) -> list[str]: domain="food_ordering", replies=["Got it — a large pepperoni pizza."], script=[ - Say("I'd like to order a large"), - Silence(3.0), # long enough that a split is the correct answer - Say("pepperoni pizza please."), + # long enough that a split is the correct answer + *fluent("I'd like to order a large", 3.0, "pepperoni pizza please."), *_SETTLE, ], expect=[UserTurns(2), NoGhostTurns(), NoErrors()], expect_by_detector={ - # Observed, with the mechanism deliberately not asserted: under `lexical` - # this merges, and the event trace shows Flux never committing the first - # fragment at all — it streams partials through the whole 3s gap and emits - # one commit. So the merge happens inside Flux, not in Timbal's HOLD. + # Observed, with the mechanism deliberately not asserted: under `lexical` and + # `local` this merges, and the event trace shows Flux never committing the + # first fragment at all — it streams partials through the whole 3s gap and + # emits one commit. So the merge happens inside Flux, not in Timbal's HOLD. # Why the same cached audio splits under `provider` is still unexplained; # `commit()` is a no-op for Flux, so it is not an obvious forced endpoint. - "lexical": [ + detector: [ Merged("I'd like to order a large pepperoni pizza please."), NoGhostTurns(), NoErrors(), - ], + ] + for detector in ("lexical", "local") }, note=( - "Splits under `provider`, merges under `lexical`, from byte-identical cached " - "audio. Consistent across runs but not yet explained — see the comment above." + "Splits under `provider`, merges under `lexical` and `local`, from byte-identical " + "cached audio. Consistent across runs but not yet explained — see the comment above." ), ), Scenario( @@ -453,9 +521,8 @@ def texts(self) -> list[str]: domain="food_ordering", replies=["A burger, fries and a chocolate milkshake. Coming up."], script=[ - Say("I'll take a burger, some fries,"), - Silence(1.4), # mid-list breath, not an end of turn - Say("and a chocolate milkshake."), + # mid-list breath, not an end of turn + *fluent("I'll take a burger, some fries,", 1.4, "and a chocolate milkshake."), *_SETTLE, ], expect=[ @@ -463,8 +530,11 @@ def texts(self) -> list[str]: NoGhostTurns(), NoErrors(), ], - known_failure={"*": _TRAILING_MODIFIER_FAILURE}, - note="A pause after a comma mid-enumeration: prosody says continue even though the gap is long.", + note=( + "A pause after a comma mid-enumeration: prosody says continue even though the " + "gap is long. Failed on every detector until fluent synthesis; now passes on all " + "three." + ), ), Scenario( id="food_barge_in", @@ -501,14 +571,17 @@ def texts(self) -> list[str]: domain="medical_intake", replies=["Thanks. Has it changed since then?"], script=[ - Say("The pain started"), - Silence(1.5), - Say("maybe on Tuesday."), + *fluent("The pain started", 1.5, "maybe on Tuesday."), *_SETTLE, ], expect=[Merged("The pain started maybe on Tuesday."), NoGhostTurns(), NoErrors()], known_failure={"*": _TRAILING_MODIFIER_FAILURE}, - note="Trailing off mid-recall, the archetypal case for holding instead of endpointing.", + intermittent=True, + note=( + "Trailing off mid-recall, the archetypal case for holding instead of " + "endpointing, and the last of its class still failing after fluent synthesis. " + "`local` merges it about one run in five, so passing proves nothing." + ), ), Scenario( id="medical_barge_in", @@ -539,9 +612,7 @@ def texts(self) -> list[str]: domain="banking", replies=["Got it, account 447291."], script=[ - Say("My account number is four four seven"), - Silence(1.4), - Say("two nine one."), + *fluent("My account number is four four seven", 1.4, "two nine one."), *_SETTLE, ], expect=[ @@ -549,11 +620,14 @@ def texts(self) -> list[str]: NoGhostTurns(min_similarity=0.4), NoErrors(), ], - known_failure={"*": "splits into three turns, one of them a spurious single-token commit (observed: 'I')"}, + known_failure={ + "provider": "Flux splits the digit string and commits a spurious single-token turn" + }, note=( "The hardest merge in the suite: a digit string broken across a pause, with no " - "words to hint continuation. Also the only scenario so far to produce a genuine " - "ghost turn, which is worth keeping precisely because it reproduces one." + "words to hint continuation. `lexical` and `local` merge it once the fragment " + "carries mid-sentence prosody; `provider` still splits and emits the one genuine " + "ghost turn the suite reproduces." ), ), Scenario( @@ -598,9 +672,7 @@ def texts(self) -> list[str]: domain="coding_help", replies=["Can you paste the traceback?"], script=[ - Say("I'm getting an error in my"), - Silence(1.5), - Say("async generator function."), + *fluent("I'm getting an error in my", 1.5, "async generator function."), *_SETTLE, ], expect=[ diff --git a/benchmarks/voice/synth.py b/benchmarks/voice/synth.py index a031fe55..befaaf4d 100644 --- a/benchmarks/voice/synth.py +++ b/benchmarks/voice/synth.py @@ -17,14 +17,17 @@ import argparse import asyncio +import base64 import hashlib +import json import logging import os import sys import wave -from collections.abc import Iterable, Iterator +from collections.abc import Iterable, Iterator, Sequence from pathlib import Path +import httpx import structlog from dotenv import load_dotenv from timbal.voice import AudioOutputConfig @@ -137,6 +140,121 @@ async def synthesize_clips( return {t: clip_path(t, voice_id, model).read_bytes() for t in wanted} +# --------------------------------------------------------------------------- +# Fluent utterances +# --------------------------------------------------------------------------- +# +# A speaker who pauses mid-sentence keeps the intonation of a sentence still in +# progress. Synthesizing the fragments separately does not: ElevenLabs renders +# each one as its own sentence and gives it a falling, finished contour. +# +# Measured with Smart Turn v3 on identical words: "I want to return an item I +# bought" scores 0.986 (finished) rendered standalone and 0.019 (mid-thought) +# when cut out of the fluent whole-sentence render. That is the difference +# between a scenario testing turn-taking and a scenario testing TTS phrasing. +# +# So fluent utterances are rendered once, whole, and sliced at the character +# timestamps ElevenLabs returns alongside the audio. + +ALIGNMENT_ENDPOINT = "https://api.elevenlabs.io/v1/text-to-speech/{voice_id}/with-timestamps" + + +def alignment_path(text: str, voice_id: str = USER_VOICE_ID, model: str = TTS_MODEL) -> Path: + return clip_path(text, voice_id, model).with_suffix(".json") + + +def part_key(utterance: str, index: int) -> str: + """Cache/clip key for one slice of a fluent utterance.""" + return f"{utterance}#{index}" + + +def _part_end_chars(parts: Sequence[str]) -> list[int]: + """Exclusive character offset of each part within ``" ".join(parts)``.""" + ends: list[int] = [] + pos = 0 + for i, part in enumerate(parts): + if i: + pos += 1 # the joining space + pos += len(part) + ends.append(pos) + return ends + + +def slice_fluent(pcm: bytes, char_end_times: Sequence[float], parts: Sequence[str]) -> list[bytes]: + """Cut ``pcm`` at the boundary where each part's last character ends. + + The final part runs to the end of the audio so no trailing samples are lost. + """ + slices: list[bytes] = [] + start = 0 + for i, end_char in enumerate(_part_end_chars(parts)): + if i == len(parts) - 1: + stop = len(pcm) + else: + # Byte offsets must stay sample-aligned or the PCM16 frames shear. + stop = min(int(char_end_times[end_char - 1] * SAMPLE_RATE) * 2, len(pcm)) + slices.append(pcm[start:stop]) + start = stop + return slices + + +async def _synthesize_aligned( + utterance: str, voice_id: str, model: str +) -> tuple[bytes, list[float]]: + """Whole-utterance PCM plus per-character end times, cached on disk. + + Uses the REST ``with-timestamps`` endpoint; the streaming websocket used for + ordinary clips does not return alignment. + """ + pcm_file = clip_path(utterance, voice_id, model) + align_file = alignment_path(utterance, voice_id, model) + if pcm_file.exists() and align_file.exists(): + return pcm_file.read_bytes(), json.loads(align_file.read_text()) + + api_key = os.environ.get("ELEVENLABS_API_KEY") + if not api_key: + raise ValueError("Set ELEVENLABS_API_KEY to synthesize fluent utterances.") + async with httpx.AsyncClient(timeout=60) as client: + response = await client.post( + ALIGNMENT_ENDPOINT.format(voice_id=voice_id), + params={"output_format": f"pcm_{SAMPLE_RATE}"}, + headers={"xi-api-key": api_key}, + json={"text": utterance, "model_id": model}, + ) + response.raise_for_status() + payload = response.json() + + pcm = base64.b64decode(payload["audio_base64"]) + ends = payload["alignment"]["character_end_times_seconds"] + CACHE_DIR.mkdir(parents=True, exist_ok=True) + pcm_file.write_bytes(pcm) + align_file.write_text(json.dumps(ends)) + return pcm, ends + + +async def synthesize_fluent( + groups: Iterable[tuple[str, Sequence[str]]], + *, + voice_id: str = USER_VOICE_ID, + model: str = TTS_MODEL, + quiet: bool = False, +) -> dict[str, bytes]: + """Return ``{part_key: pcm}`` for each ``(utterance, parts)`` group.""" + wanted = {utterance: tuple(parts) for utterance, parts in groups} + if not wanted: + return {} + missing = [u for u in wanted if not alignment_path(u, voice_id, model).exists()] + if missing and not quiet: + print(f"synthesizing {len(missing)} fluent utterance(s) with alignment...") + + clips: dict[str, bytes] = {} + for utterance, parts in wanted.items(): + pcm, ends = await _synthesize_aligned(utterance, voice_id, model) + for i, chunk in enumerate(slice_fluent(pcm, ends, parts)): + clips[part_key(utterance, i)] = chunk + return clips + + # --------------------------------------------------------------------------- # CLI # --------------------------------------------------------------------------- @@ -170,6 +288,21 @@ def _build(clips: dict[str, bytes]) -> bytes: checks.append(("silence is exact", duration_secs(gap) == 0.5, f"{len(gap)} bytes")) checks.append(("frames round-trip", b"".join(frames(a)) == a, f"{len(a) // FRAME_BYTES} frames")) + # Slicing a fluent utterance must lose no audio and stay on PCM16 sample + # boundaries, or every downstream fragment shears by half a sample. + parts = ("Verification clip one,", "sliced in two.") + utterance = " ".join(parts) + pcm, ends = await _synthesize_aligned(utterance, USER_VOICE_ID, TTS_MODEL) + pieces = slice_fluent(pcm, ends, parts) + checks.append(("fluent slice is lossless", b"".join(pieces) == pcm, f"{len(pcm)} bytes")) + checks.append( + ( + "fluent slice is sample-aligned", + all(len(p) % 2 == 0 for p in pieces), + " + ".join(f"{duration_secs(p):.2f}s" for p in pieces), + ) + ) + for name, ok, detail in checks: print(f" {'ok ' if ok else 'FAIL'} {name:<24} {detail}") failed = [name for name, ok, _ in checks if not ok] From 5b967e35a9e4f40287a1648ac9ec903879f1395a Mon Sep 17 00:00:00 2001 From: berges99 Date: Sat, 25 Jul 2026 18:46:23 +0200 Subject: [PATCH 03/30] feat(bench): cross 3 STT backends x 4 detectors over 38 scenarios --stt and --detector now cross into cells, each with its own scorecard, baseline entry and gate, plus a scenario x cell grid and within-cell flaky detection. --jobs overlaps the whole queue. Parallelism turned out to be nearly free, contradicting the assumption --jobs was built under. Across four full-suite runs, two serial and two at --jobs 4, p50 landed in 214-235ms serial and 213-222ms parallel: two serial runs of one cell differ as much as serial differs from parallel. Elapsed went 426s -> 114s. Real-time pacing is why - a replayed session is asleep between 20ms frames, so sessions interleave in the gaps instead of competing for inference. The guard stays regardless: --update-baseline is refused above --jobs 1 and latency is never compared across differing concurrency, neither of which the gate can verify at compare time. Widening to Nova and ElevenLabs reversed the detector verdict. Flux does turn detection itself, so all four detectors land within 10 points there and the conclusion drawn from that column - that the audio EOU buys nothing Namo does not already provide - was an artifact of the backend. On the two backends that return transcripts without deciding turns, local leads (89/79/87% against lexical's 92/68/89%) and provider collapses to 61/64%, scoring 0% on mid-sentence pauses because it defers to an STT that is not endpointing. Smart Turn earns its keep exactly where the STT does not endpoint for you. Two expectations were quietly wrong once a second provider existed. banking_digits failed in seven of twelve cells having committed exactly one turn in all twelve, because Flux writes "four four seven" where Nova writes "447" - and the suite had already been bitten by this and fixed it by rewriting the script to match Flux, the one fix that cannot survive another provider. normalize() now spells digit runs out. food_long_pause demanded a merge because that had been seen on Flux, so Nova failed it for splitting a 3.0s pause; it now asserts ContentPreserved rather than a turn count. Marker keys resolve cell-first (deepgram-nova/lexical, then deepgram-nova/*, then lexical, then *) so a Flux observation cannot excuse another backend again. The scenario library goes 21 -> 38, aimed at the edges: barge-in at 150ms, a one-word "Stop.", two interruptions in one session, an interruption made of the assistant's own words, a backchannel that must not interrupt, three-part sentences, self-corrections, a 12s run-on, two finished sentences 0.9s apart, and pure silence. Barge-in survived all of it - 36/36 in every backend, including the one-word case that MIN_BARGE_IN_PARTIAL_WORDS should have dropped, because the commit still lands even when the partial is ignored. Five scenarios had been confirming a solved problem; every new failure is a stop mid-thought. The most useful find is that the metric was hiding failures. coding_double_pause passed on ElevenLabs having dropped "inside a test" entirely: whole-string similarity scored the remainder 0.84 against the full sentence, over the 0.8 bar. The same bug passed banking_digits_pause with "291" missing from an account number. Merged and ContentPreserved now match each spoken fragment against its best transcript window, where a dropped part scores 0.40 instead of 0.84. Two green cells were lying. Three new failures belong to the STT, landing identically under all four detectors: Nova transcribes and commits "mm-hmm" so an acknowledgement silences the assistant, Nova endpoints at clause boundaries inside a 12s run-on, and ElevenLabs merges two finished sentences 0.9s apart. Timbal has no notion of a backchannel at all. Two older findings sharpened: the ghost single-token 'I' turn under Flux + provider was blamed on digit strings until medical_filler_midway reproduced it verbatim on ordinary words, and --repeat 3 caught coding_pause splitting 1-in-3 under provider after it had sat in the baseline as a clean pass, having only ever been run once per cell. No product code changes. All three Flux cells re-baselined serially at 100% - lexical 34/34, local 32/32, provider 27/27, p50 226-228ms, zero ghost turns, zero errors. Nova and ElevenLabs are measured every run but not baselined; their genuine failures need per-cell markers first. Known failures 3 -> 10 of 38, eight scoped to specific cells and eight intermittent, which is worth watching: a suite that marks everything interesting gates nothing. --- benchmarks/voice/README.md | 297 ++++++++++++++++-- benchmarks/voice/baseline.json | 120 +++++--- benchmarks/voice/cli.py | 235 +++++++++----- benchmarks/voice/harness.py | 2 +- benchmarks/voice/scenario.py | 544 +++++++++++++++++++++++++++++++-- benchmarks/voice/score.py | 96 +++++- benchmarks/voice/synth.py | 4 +- 7 files changed, 1127 insertions(+), 171 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 365017f6..76b1725d 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -18,7 +18,7 @@ mock STT. That covers the session state machine and nothing below it — no audi no real STT connection, no VAD, no endpointing. The bugs that actually reach production live in that gap. -## Status: 21 scenarios across 5 domains, scoring and gating in place +## Status: 38 scenarios across 5 domains, matrix, scoring and gating in place | File | Role | |---|---| @@ -28,7 +28,7 @@ production live in that gap. | `score.py` | JSONL records, scorecard aggregation, baseline diffing | | `cli.py` | runner, reporting, regression gate | -Still to come: the config matrix with parallelism, and AEC-leak simulation. +Still to come: AEC-leak simulation. ## What it found @@ -103,27 +103,205 @@ one — both are Namo 0.00 plus a provider-added period, so nothing separates th Left alone. `banking_confirmation` intermittently splits "Yes, that's correct." in two with a -self-barge-in, and `banking_digits_pause` under `provider` still emits the one -genuine ghost turn the suite reproduces. Both are recorded as known failures with -written reasons, scoped to the detectors where they actually occur, so they report -on every run without blocking the gate. +self-barge-in, and `banking_digits_pause` under `provider` emits the one genuine +ghost turn the suite reproduces. Both are recorded as known failures with written +reasons, scoped to the detectors where they actually occur, so they report on +every run without blocking the gate. + +The digit-string one is a good argument for `--repeat`. A single run showed it +passing and the marker looked stale; at `--repeat 6` it merged 5 times and split +once, emitting a ghost `'I'`. A rate like that is invisible to any single run in +either direction — it would read as fixed five times out of six and as reliably +broken the sixth. It is marked `intermittent` so passing no longer reports as an +unexpected pass, since passing genuinely proves nothing here. + +**Adding a second STT backend broke seven cells that were working correctly.** +`banking_digits` failed in seven of twelve cells while committing exactly one turn +in all twelve: Flux writes "four four seven two nine one" and Nova writes "447291" +for the same audio. Perfect turn-taking, reported as a turn-taking defect. The +suite had already been bitten by this once and fixed it by rewriting the script to +match Flux's spelling, which is precisely the fix that does not survive a second +provider. `normalize()` now spells digit runs out, so the comparison is +representation-independent. + +**A scenario was quietly grading providers against each other's habits.** +`food_long_pause` asserted a merge under `lexical` and `local` because that had +been *observed* on Flux, so Nova failed it for splitting a 3.0s pause — which is +perfectly defensible behavior, and which the trace showed Flux never even gave a +detector the chance to get wrong. At that gap neither answer is knowably right: +holding costs 3s of dead air, splitting sends a fragment to the LLM. It now asserts +`ContentPreserved` — everything spoken arrived, across however many turns — which +still fails ElevenLabs for dropping half the order while letting both turn-taking +policies pass. Any expectation that encodes an observation rather than a +requirement will do this as soon as the matrix widens. Three cells are baselined so far: | cell | gated | p50 | p95 | known failures | |---|---|---:|---:|---:| -| `deepgram-flux/local` | 19/19 | 228ms | 300ms | 2 | -| `deepgram-flux/lexical` | 19/19 | 230ms | 301ms | 2 | -| `deepgram-flux/provider` | 16/16 | 222ms | 326ms | 3 | - -The three are indistinguishable at the median now. `provider` carries the extra -known failure — it is the only configuration that still splits a digit string -across a pause and emits the one ghost turn the suite reproduces — and it has the -longest tail, so it still looks like the wrong default on Flux. `local` and -`lexical` are otherwise equivalent here, which means the audio EOU is not currently -buying anything Namo does not already provide, at least on Flux with clean audio. -Three cells is not a matrix; worth confirming across STT backends before changing -any default. +| `deepgram-flux/local` | 19/19 | 214ms | 283ms | 2 | +| `deepgram-flux/lexical` | 19/19 | 235ms | 328ms | 2 | +| `deepgram-flux/provider` | 16/16 | 234ms | 324ms | 3 | + +The three are indistinguishable at the median: the 21ms spread is inside the ±6% +drift two identical serial runs show (see below), so nobody should read a winner +out of this column. + +### Measuring only Flux was measuring Flux + +The Flux column cannot tell detectors apart, because Flux does turn detection +itself. Every detector scores 95–100% on it, and the reasonable-looking conclusion +from that column alone — "the audio EOU buys nothing Namo doesn't already provide" +— was an artifact of the choice of backend. Running the same 21 scenarios against +Nova and ElevenLabs, which return transcripts without deciding turns, separates +them immediately (2 repeats, 456 runs): + +| detector | Flux | Nova | ElevenLabs | +|---|---:|---:|---:| +| `heuristic` | 95% | 79% | 79% | +| `local` | **100%** | **89%** | **95%** | +| `lexical` | 100% | 76% | 87% | +| `provider` | 97% | 75% | 75% | + +`local` wins every column. Restricting to the mid-sentence pause merges, the only +family where detectors differ at all, makes the mechanism plain: + +| detector | Flux | Nova | ElevenLabs | +|---|---:|---:|---:| +| `heuristic` | 80% | 20% | 20% | +| `local` | 100% | **60%** | **80%** | +| `lexical` | 100% | 20% | 70% | +| `provider` | 100% | **0%** | **0%** | + +`provider` goes from perfect to zero. That is the expected result stated plainly: +it defers to the STT, and off Flux there is nothing to defer to. Every other +scenario family is flat — barge-in is 90–100% in all twelve cells — so pause +merging carries the entire discriminating signal in the suite. + +The real finding is that **Smart Turn earns its keep precisely where the STT does +not endpoint for you**, which is invisible on Flux. `local` beats `lexical` by 40 +points on Nova and 10 on ElevenLabs: hearing that the speaker's pitch is still +mid-phrase survives a transcript that reads like a finished sentence, and text +alone does not. If Timbal is ever pointed at a plain streaming ASR, `local` is the +default and `provider` is close to unusable for pauses. + +Two caveats. Nova and ElevenLabs are not baselined — several cells have genuine +failures that would need per-cell `known_failure` markers first, so only the Flux +column is gated today. And ElevenLabs drops content on hard inputs independently of +turn-taking (it committed "I'd like to order a large" and silently lost the pizza), +which `ContentPreserved` now catches but which is an STT-quality difference rather +than a turn-taking one. + +The ranking survived the suite growing to 38 (numbers are not comparable to the +table above — the added scenarios are deliberately harder): `local` 92/81/92, +`lexical` 94/71/89, `heuristic` 89/65/76, `provider` 91/63/75. `local` still wins +both non-Flux columns by 10 points or more; `lexical` edges it by 2 on Flux, where +the backend is doing the work anyway. + +### Harder cases: 21 → 38 scenarios + +Barge-in scored 90–100% in all twelve cells, which meant five scenarios were +spending real time confirming something already known. Seventeen were added to +attack the edges instead: barge-in at 150ms instead of a comfortable 600, a +one-word "Stop.", two interruptions in one session, an interruption made of the +assistant's own words, a backchannel that must *not* interrupt, three-part +sentences, self-corrections, a 12-second run-on, two finished sentences 0.9s +apart that must not merge, and four seconds of pure silence. + +**Barge-in survived all of it.** Instant, one-word, double and echoing barge-ins +pass in all twelve cells, as do pure silence, a bare "No." and a follow-up taken +after the assistant stops. The one-word case is the surprising pass: +`MIN_BARGE_IN_PARTIAL_WORDS` drops single-word *partials* as mic blips, so "Stop." +should have been ignored — the commit still arrives and still cuts the assistant +off. The gate delays a one-word barge-in rather than losing it. + +Every new failure is a stop mid-thought, and the detector rankings barely move +(17 new scenarios, 12 cells): + +| detector | Flux | Nova | ElevenLabs | +|---|---:|---:|---:| +| `heuristic` | 82% | 47% | 70% | +| `local` | 82% | **70%** | **88%** | +| `lexical` | 88% | 64% | 88% | +| `provider` | 82% | 47% | 70% | + +**The metric was hiding failures.** `coding_double_pause` passed on ElevenLabs +having committed "The build fails when I import the module" — "inside a test" +simply gone. Whole-string similarity scored that 0.84 against the full sentence, +over the 0.8 bar, so a third of the utterance vanished and the suite called it a +clean merge. The same bug was passing `banking_digits_pause` on ElevenLabs at 0.85 +while "291" was dropped from an account number. `Merged` and `ContentPreserved` +now check each spoken fragment against its best-matching window of the transcript, +where a missing part matches nothing and scores 0.40. Both of those are now +correctly red. A similarity threshold over a long string cannot see a dropped +tail, and the longer the utterance the blinder it gets. + +Three findings are the STT's, identical under all four detectors: + +- **Nova commits backchannels.** "Mm-hmm" over the assistant is transcribed and + committed, and every detector then treats it as a barge-in and stops the reply. + Flux and ElevenLabs swallow the sound and pass. Timbal has no notion of a + backchannel, so on any STT that transcribes one, an acknowledgement silences the + assistant. +- **Nova endpoints at sentence boundaries.** The 12-second run-on comes back as + three turns, split at clause boundaries inside continuous speech. +- **ElevenLabs merges finished sentences.** "I'll have a coffee." and "Actually, + make it two." 0.9s apart come back as one turn in all four cells. Its endpointer + waits longer than Flux's, which helps on pauses and hurts here — the suite had + no scenario punishing an over-merge before this, so a detector could have scored + well by holding everything. + +Two findings sharpen older ones. The spurious single-token `'I'` turn under Flux + +`provider` had been attributed to digit strings for as long as +`banking_digits_pause` was the only scenario producing it; `medical_filler_midway` +now produces it verbatim on ordinary words, so it is the path, not the content. +And running the baselined cells at `--repeat 3` caught `coding_pause` splitting +once in three under `provider` — a scenario baselined as a clean pass, unchanged, +that had only ever been run once per cell. + +The trailing-modifier failure now has four instances rather than one, and they +agree: `medical_hesitant_pause`, `medical_self_correction`, `banking_correction` +and `coding_double_pause` all commit a fragment that is a complete sentence in +isolation, and no text signal argues for holding. `banking_correction` is the one +with teeth — split, the agent transfers to account 447 when the caller said 448 — +and it is also the clearest win for Namo anywhere in the suite: `lexical` merges it +3/3 on Flux where `local` and `provider` never do. + +Known failures went from 3 to 10 of 38, which is worth watching. Eight of the ten +are scoped to specific cells rather than blanket-marked, and eight are +`intermittent` — but a suite that marks everything interesting gates nothing, and +this is the point at which that stops being a theoretical concern. + +**Parallelism turned out to be nearly free, which was not the expectation.** +`--jobs` was built assuming concurrent sessions would contend for Silero and Smart +Turn inference and inflate `eou→audio`, so the gate refuses to compare runs +measured at different concurrency. Then the full suite was run four times, twice +each way — p50 per cell, in run order: + +| cell | serial | serial | `--jobs 4` | `--jobs 4` | +|---|---:|---:|---:|---:| +| `deepgram-flux/local` | 228ms | 214ms | 214ms | 217ms | +| `deepgram-flux/lexical` | 230ms | 235ms | 213ms | 214ms | +| `deepgram-flux/provider` | 222ms | 234ms | 222ms | 215ms | + +Two serial runs of the same cell differ by up to 6%, which is as large as any +serial-to-parallel gap — and the parallel runs are, if anything, slightly faster +and tighter (213–222ms, against 214–235ms serial). There is no separation to find +here. + +Real-time pacing is why: a replayed session spends nearly all of its wall clock +asleep between 20ms frames, so four of them interleave in the gaps rather than +competing for CPU. The same 54 runs take 426s serially and 114s at `--jobs 4`, a +3.7× speedup that costs nothing measurable. + +The guard stays anyway. It costs one serial run before committing a baseline, and +the headroom above is specific to this machine, this suite size and `--jobs 4` — +none of which the gate can verify at compare time. It fails toward reporting a +number rather than gating on one. + +The same table is a warning about the latency figures generally: a 15% gate on a +statistic that drifts 6% between identical runs has less headroom than it looks +like, and any cross-detector comparison under ~20ms is noise. ## Running @@ -141,10 +319,53 @@ uv run python benchmarks/voice/cli.py --repeat 3 # variance + flaky uv run python benchmarks/voice/cli.py --quiet # results only uv run python benchmarks/voice/cli.py --dump # WAVs to results/dumps/ uv run python benchmarks/voice/cli.py --update-baseline # accept current behavior + +# the matrix: --stt and --detector are crossed, one scorecard per cell +uv run python benchmarks/voice/cli.py --detector local,lexical,provider --jobs 4 ``` Exit code is non-zero when any expectation fails or a regression is gated. +## The matrix + +`--stt` and `--detector` take comma-separated lists and are crossed, producing one +scorecard, one baseline entry and one gate per cell, plus a scenario × cell grid at +the end. The grid is the point: a row tells you whether a scenario fails everywhere +(Timbal's problem) or in one column (that provider's problem), which no amount of +staring at a single cell will tell you. + +``` + 1 2 3 + banking_digits_pause ✓ ✓ x + banking_hesitation ✓ ✓ · + medical_hesitant_pause x x x + + 1 deepgram-flux/local 19/19 p50 214ms + 2 deepgram-flux/lexical 19/19 p50 213ms + 3 deepgram-flux/provider 16/16 p50 222ms + + ✓ pass ✗ FAIL x known failure ! XPASS ~ flaky · not run +``` + +`x` and `✗` are deliberately different glyphs: a row of `x` is a documented +limitation, a single `✗` is a regression. `·` means the scenario opted out of that +detector (see *Per-detector expectations*). + +`known_failure` and `expect_by_detector` keys are matched most-specific-first: +`"deepgram-nova/lexical"`, then `"deepgram-nova/*"`, then `"lexical"`, then `"*"`. +Scope findings to a cell whenever they came from one — a bare detector key silently +applies a Flux observation to every other backend, which is how `food_long_pause` +came to fail Nova for behaving reasonably. The `"deepgram-nova/*"` rung is for +failures that are the STT's alone and land identically under all four detectors, +like Nova committing a "mm-hmm"; writing those per cell states one fact four times +and hides that it is one fact. + +`--jobs N` overlaps runs across the whole queue, cells included. Two rules keep it +from corrupting the thing it accelerates: `--update-baseline` is refused above +`--jobs 1`, and latency is never compared across differing concurrency — it is +printed with a note instead. Pass rates and ghost turns still gate normally, so a +parallel matrix run is a real gate on everything except speed. + ## Results and the regression gate Every run appends one JSON line per scenario to `results/run-.jsonl`, @@ -160,6 +381,7 @@ STT providers drift under us and yesterday's ceiling is tomorrow's false alarm: | a scenario's pass rate drops | speedups | | ghost turns increase | brand-new scenarios (nothing to compare) | | median latency worsens >15% | latency with fewer than 20 samples | +| | latency measured at a different `--jobs` than the baseline | **Latency gates on p50, not p95.** With ~8 latency samples, p95 is the maximum in disguise: one slow turn moved it 394ms → 477ms on an unchanged tree while all five @@ -175,10 +397,18 @@ Measured on this suite, p50 is worth gating and the tail is not — two independ | p95 | 383ms | 375ms | 2% | | max | 462ms | 378ms | 18% | -At 20 scenarios a single pass produces 28 latency samples, so `--repeat 1` clears -the floor on its own. Repeats still buy flaky detection: any scenario that passes -some repeats and fails others is reported by name as **FLAKY** — usually a real -race rather than a bad test. +At 38 scenarios a single pass produces well over 40 latency samples, so +`--repeat 1` clears the floor on its own. Repeats still buy flaky detection: any +scenario that passes some repeats and fails others is reported by name as +**FLAKY** — usually a real race rather than a bad test. This is not optional +rigour: `coding_pause` sat in the baseline as a clean pass until `--repeat 3` +caught it splitting once in three under `provider`. + +Flaky detection deliberately looks *within* a cell, not across cells. Two detectors +disagreeing is the matrix working as designed; the same detector disagreeing with +itself is a race. It also covers known failures, which the per-cell scorecard +cannot see — those are excluded from `per_scenario` by design, which is how a +marked scenario passing 5 runs in 6 stays invisible until you ask for repeats. ## Known failures @@ -249,11 +479,24 @@ the provider's commit means a bare "Um..." legitimately starts a turn. ## What the current library measures -`pause` (1.6s gap, merges) and `long_pause` (3.0s gap, splits) bracket Deepgram -Flux's turn window between those two durations. `barge_in` and `barge_in_late` -interrupt the same reply at 600ms and 2500ms, yielding heard prefixes of ~39 and -~77 characters — which is how you check the truncation path scales with real -playback position. +Scenarios come in matched sets, because a single data point about turn-taking is +rarely interpretable on its own. + +Pause length is swept at 0.6s, 1.2–1.5s and 3.0s (`support_pause_short`, the +`*_pause` family, `food_long_pause`), which brackets each backend's turn window +and separates "merges anything" from "merges what a speaker would". Barge-in is +swept by offset at 150ms, 600ms and 2500ms against the same reply, yielding heard +prefixes from nothing to ~77 characters — which is how you check the truncation +path scales with real playback position — and by shape: one word, twice in a +session, echoing the assistant's own words, and a backchannel that must not +interrupt at all. + +Each family also carries its own inverse, so a detector cannot score well by +always guessing the same way. Against the pause merges sit `food_rapid_fire` (two +finished sentences 0.9s apart, must split) and `medical_long_utterance` (12 +unbroken seconds, must not). Against the barge-ins sits `food_backchannel`. +Against every commit sits `support_silence_only`, which says an open mic with no +speech produces no turn at all. ## Voices diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index 88bf6761..a8f08687 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -3,129 +3,181 @@ "label": "deepgram-flux/lexical", "stt": "deepgram-flux", "detector": "lexical", - "runs": 19, - "passed": 19, + "runs": 34, + "passed": 34, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 229.9, - "latency_p95": 301.2, - "latency_min": 184.6, - "latency_max": 373.8, - "latency_samples": 25, + "latency_p50": 227.8, + "latency_p95": 330.2, + "latency_min": 171.4, + "latency_max": 432.0, + "latency_samples": 50, "per_scenario": { + "banking_correction": 1.0, "banking_digits": 1.0, "banking_digits_pause": 1.0, "banking_hesitation": 1.0, + "banking_short_reject": 1.0, "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, "coding_pause": 1.0, "coding_simple": 1.0, + "food_backchannel": 1.0, "food_barge_in": 1.0, "food_list_pause": 1.0, "food_long_pause": 1.0, "food_pause": 1.0, + "food_rapid_fire": 1.0, "food_simple": 1.0, + "food_trailing_preposition": 1.0, "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_filler_midway": 1.0, "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, "medical_simple": 1.0, "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, "support_closer": 1.0, "support_pause": 1.0, - "support_simple": 1.0 + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0, + "support_trailing_conjunction": 1.0 }, "flaky": [], "known_failures": [ "banking_confirmation", - "medical_hesitant_pause" + "coding_double_pause", + "medical_hesitant_pause", + "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 135.3 + "wall_secs": 268.9, + "jobs": 1 }, "deepgram-flux/local": { "label": "deepgram-flux/local", "stt": "deepgram-flux", "detector": "local", - "runs": 19, - "passed": 19, + "runs": 32, + "passed": 32, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 227.8, - "latency_p95": 299.8, - "latency_min": 185.0, - "latency_max": 308.9, - "latency_samples": 25, + "latency_p50": 226.8, + "latency_p95": 291.8, + "latency_min": 164.7, + "latency_max": 356.3, + "latency_samples": 52, "per_scenario": { "banking_digits": 1.0, "banking_digits_pause": 1.0, "banking_hesitation": 1.0, + "banking_short_reject": 1.0, "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, "coding_pause": 1.0, "coding_simple": 1.0, "food_barge_in": 1.0, "food_list_pause": 1.0, "food_long_pause": 1.0, "food_pause": 1.0, + "food_rapid_fire": 1.0, "food_simple": 1.0, + "food_trailing_preposition": 1.0, "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_filler_midway": 1.0, "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, "medical_simple": 1.0, "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, "support_closer": 1.0, "support_pause": 1.0, - "support_simple": 1.0 + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0, + "support_trailing_conjunction": 1.0 }, "flaky": [], "known_failures": [ "banking_confirmation", - "medical_hesitant_pause" + "banking_correction", + "coding_double_pause", + "food_backchannel", + "medical_hesitant_pause", + "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 132.6 + "wall_secs": 262.0, + "jobs": 1 }, "deepgram-flux/provider": { "label": "deepgram-flux/provider", "stt": "deepgram-flux", "detector": "provider", - "runs": 16, - "passed": 16, + "runs": 27, + "passed": 27, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 222.1, - "latency_p95": 326.4, - "latency_min": 187.3, - "latency_max": 357.2, - "latency_samples": 27, + "latency_p50": 226.4, + "latency_p95": 320.8, + "latency_min": 171.1, + "latency_max": 396.6, + "latency_samples": 51, "per_scenario": { "banking_digits": 1.0, + "banking_short_reject": 1.0, "coding_barge_in": 1.0, - "coding_pause": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, "coding_simple": 1.0, + "food_backchannel": 1.0, "food_barge_in": 1.0, "food_list_pause": 1.0, "food_long_pause": 1.0, "food_pause": 1.0, + "food_rapid_fire": 1.0, "food_simple": 1.0, + "food_trailing_preposition": 1.0, "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_long_utterance": 1.0, "medical_simple": 1.0, "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, "support_closer": 1.0, "support_pause": 1.0, - "support_simple": 1.0 + "support_silence_only": 1.0, + "support_simple": 1.0, + "support_trailing_conjunction": 1.0 }, "flaky": [], "known_failures": [ "banking_confirmation", + "banking_correction", "banking_digits_pause", - "medical_hesitant_pause" + "coding_double_pause", + "coding_pause", + "medical_filler_midway", + "medical_hesitant_pause", + "medical_self_correction", + "support_pause_short" ], - "unexpected_passes": [ - "banking_digits_pause" - ], - "wall_secs": 118.8 + "unexpected_passes": [], + "wall_secs": 247.6, + "jobs": 1 } } diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index af467600..75677cde 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -8,14 +8,22 @@ uv run python benchmarks/voice/cli.py # all scenarios uv run python benchmarks/voice/cli.py -s barge_in -s pause # a subset uv run python benchmarks/voice/cli.py --detector lexical # Timbal's HOLD path + uv run python benchmarks/voice/cli.py --detector local,lexical,provider --jobs 4 uv run python benchmarks/voice/cli.py --repeat 3 # variance + flaky detection uv run python benchmarks/voice/cli.py --update-baseline # accept current behavior uv run python benchmarks/voice/cli.py --quiet # results only uv run python benchmarks/voice/cli.py --dump # WAVs per run +``--stt`` and ``--detector`` take comma-separated lists and are crossed into a +matrix, one scorecard and one baseline entry per cell. A row of the resulting grid +answers the question a single cell cannot: whether a scenario fails because Timbal +is wrong or because one provider is. + Replay runs in real time — the STT provider keeps its own wall clock and Silero needs an unbroken stream — so a scenario costs roughly what the conversation -would cost a human. +would cost a human. ``--jobs`` overlaps runs to claw that back, at the cost of +latency fidelity: concurrent sessions contend for the same ONNX inference, so +those numbers are reported but never gated (§ ``score.compare``). Exit code is non-zero when an expectation fails or a regression is gated. """ @@ -27,14 +35,18 @@ import logging import sys import time +from dataclasses import dataclass import structlog from dotenv import load_dotenv from harness import HarnessConfig, RunResult, run_scenario -from scenario import SCENARIOS, select +from scenario import SCENARIOS, Scenario, select from score import ( + RunRecord, build_scorecard, compare, + cross_cell_flaky, + format_grid, format_scorecard, load_baseline, record, @@ -44,25 +56,45 @@ from synth import synthesize_clips, synthesize_fluent -def _report(result: RunResult, known_failure: str | None, intermittent: bool = False) -> None: - print() - print(f" turns: {result.committed}") +def _report(result: RunResult, known_failure: str | None, intermittent: bool = False) -> list[str]: + lines = ["", f" turns: {result.committed}"] if result.interrupted: - print(f" heard: {result.heard_text!r}") + lines.append(f" heard: {result.heard_text!r}") if result.latencies_ms: - print(f" eou→audio: {', '.join(f'{v:.0f}ms' for v in result.latencies_ms)}") - print(f" audio: {result.audio_chunks} chunks, {result.audio_bytes} bytes") - print(f" wall: {result.wall_secs:.1f}s") - for failure in result.failures: - print(f" ✗ {failure}") + lines.append(f" eou→audio: {', '.join(f'{v:.0f}ms' for v in result.latencies_ms)}") + lines.append(f" audio: {result.audio_chunks} chunks, {result.audio_bytes} bytes") + lines.append(f" wall: {result.wall_secs:.1f}s") + lines.extend(f" ✗ {failure}" for failure in result.failures) if known_failure and not result.passed: - print(f" KNOWN FAIL (not gated): {known_failure}") + lines.append(f" KNOWN FAIL (not gated): {known_failure}") elif known_failure and intermittent: - print(" PASS (known intermittent failure — passing proves nothing)") + lines.append(" PASS (known intermittent failure — passing proves nothing)") elif known_failure: - print(" XPASS — known failure now passes, drop the known_failure marker") + lines.append(" XPASS — known failure now passes, drop the known_failure marker") else: - print(f" {'PASS' if result.passed else 'FAIL'}") + lines.append(f" {'PASS' if result.passed else 'FAIL'}") + return lines + + +def _values(flags: list[str] | None, default: str) -> list[str]: + """Flatten repeated and comma-separated flags, order preserved, deduplicated.""" + if not flags: + return [default] + out = [part.strip() for flag in flags for part in flag.split(",") if part.strip()] + return list(dict.fromkeys(out)) + + +@dataclass +class _Job: + config: HarnessConfig + scenario: Scenario + repeat: int + repeats: int + + @property + def header(self) -> str: + suffix = f" repeat {self.repeat + 1}/{self.repeats}" if self.repeats > 1 else "" + return f"\n=== {self.scenario.id} ({self.config.label}){suffix} ===" def _list_scenarios() -> int: @@ -86,10 +118,13 @@ def _list_scenarios() -> int: async def main() -> int: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("-s", "--scenario", action="append", help="scenario id (repeatable)") - parser.add_argument("--stt", default="deepgram-flux", help="elevenlabs | deepgram-flux | deepgram-nova") - parser.add_argument("--detector", default="provider", help="heuristic | provider | lexical | local") + parser.add_argument("--stt", action="append", help="elevenlabs | deepgram-flux | deepgram-nova (comma-separated)") + parser.add_argument("--detector", action="append", help="heuristic | provider | lexical | local (comma-separated)") parser.add_argument("--language", default="en") parser.add_argument("--repeat", type=int, default=1, help="runs per scenario (variance / flaky detection)") + parser.add_argument( + "--jobs", type=int, default=1, help="concurrent runs; latency is reported but not gated above 1" + ) parser.add_argument("--dump", action="store_true", help="write input/output WAVs per run") parser.add_argument("--quick", action="store_true", help="representative subset (one per domain)") parser.add_argument("--quiet", action="store_true", help="hide the per-event stream") @@ -110,81 +145,137 @@ async def main() -> int: wrapper_class=structlog.make_filtering_bound_logger(logging.DEBUG if args.verbose else logging.WARNING) ) - config = HarnessConfig(stt=args.stt, detector=args.detector, language=args.language, dump=args.dump) - selected, skipped = select(args.scenario, config.detector, quick=args.quick) - if not selected: - print(f"nothing to run for detector={config.detector}; scenarios: {[s.id for s in SCENARIOS]}") - return 2 + jobs = max(1, args.jobs) + repeats = max(1, args.repeat) + cells = [ + HarnessConfig(stt=stt, detector=detector, language=args.language, dump=args.dump) + for stt in _values(args.stt, "deepgram-flux") + for detector in _values(args.detector, "provider") + ] if args.update_baseline and (args.scenario or args.quick): # A baseline entry is replaced wholesale, so accepting a filtered run would # silently drop every scenario it didn't cover and disarm their gates. print("refusing to update the baseline from a filtered run: it would drop the other scenarios") return 2 + if args.update_baseline and jobs > 1: + # The baseline carries the latency the gate compares against. Recording it + # under contention would bake in whatever else the machine was doing. + print("refusing to update the baseline from a parallel run: measure latency at --jobs 1") + return 2 + + queue: list[_Job] = [] + skipped: list[tuple[HarnessConfig, Scenario]] = [] + for config in cells: + selected, cell_skipped = select(args.scenario, config.detector, quick=args.quick) + skipped.extend((config, s) for s in cell_skipped) + queue.extend(_Job(config, scenario, repeat, repeats) for repeat in range(repeats) for scenario in selected) + if not queue: + detectors = ", ".join(sorted({c.detector for c in cells})) + print(f"nothing to run for detector(s) {detectors}; scenarios: {[s.id for s in SCENARIOS]}") + return 2 + + wanted = {job.scenario.id: job.scenario for job in queue}.values() + clips = await synthesize_clips([text for s in wanted for text in s.standalone_texts()]) + clips |= await synthesize_fluent([g for s in wanted for g in s.fluent_groups()]) - clips = await synthesize_clips([text for s in selected for text in s.standalone_texts()]) - clips |= await synthesize_fluent([g for s in selected for g in s.fluent_groups()]) + if len(cells) > 1 or jobs > 1: + print(f"\n{len(queue)} run(s) across {len(cells)} cell(s) at --jobs {jobs}") - records = [] + # Serial keeps the live event stream, which is the whole debugging story for a + # single scenario. Concurrent runs buffer it, because interleaved streams from + # four sessions are unreadable and worse than none. + live = jobs == 1 and not args.quiet + semaphore = asyncio.Semaphore(jobs) started = time.monotonic() - for repeat in range(max(1, args.repeat)): - for scenario in selected: - suffix = f" repeat {repeat + 1}/{args.repeat}" if args.repeat > 1 else "" - print(f"\n=== {scenario.id} ({config.label}){suffix} ===") + + async def run(job: _Job) -> RunRecord: + async with semaphore: + if live: + print(job.header) t0 = time.monotonic() + buffer: list[str] = [] - def log(kind: str, detail: str = "", t0=t0) -> None: - if not args.quiet: - print(f" [+{time.monotonic() - t0:6.2f}s] {kind:<18}{detail}") + def log(kind: str, detail: str = "") -> None: + if args.quiet: + return + line = f" [+{time.monotonic() - t0:6.2f}s] {kind:<18}{detail}" + print(line) if live else buffer.append(line) - result = await run_scenario(scenario, clips, config, log=log) - _report(result, scenario.known_failure_reason(config.detector), scenario.intermittent) - records.append(record(scenario, result, repeat=repeat)) + result = await run_scenario(job.scenario, clips, job.config, log=log) + known = job.scenario.known_failure_reason(job.config.detector, job.config.stt) + report = _report(result, known, job.scenario.intermittent) + if live: + print("\n".join(report)) + else: + print("\n".join([job.header, *buffer, *report])) + return record(job.scenario, result, repeat=job.repeat, jobs=jobs) - for scenario in skipped: - print(f"\n=== {scenario.id} SKIPPED (not meaningful for {config.detector}) ===") + records = list(await asyncio.gather(*(run(job) for job in queue))) + + for config, scenario in skipped: + print(f"\n=== {scenario.id} ({config.label}) SKIPPED (not meaningful for {config.detector}) ===") if scenario.note: print(f" {scenario.note}") - card = build_scorecard(records) path = write_jsonl(records) + baseline = load_baseline() + cards = [] + exit_code = 0 + + for config in cells: + cell_records = [r for r in records if f"{r.stt}/{r.detector}" == config.label] + if not cell_records: + continue + card = build_scorecard(cell_records) + cards.append(card) - print(f"\n{'─' * 72}") - print(format_scorecard(card)) - for name in card.known_failures: - reason = next(s.known_failure_reason(config.detector) for s in selected if s.id == name) - print(f" known: {name} — {reason}") - print(f" elapsed: {time.monotonic() - started:.0f}s results: {path}") - - if args.update_baseline: - if card.pass_rate < 1.0: - # Saving here would record the failure as the accepted status quo and - # disarm its gate. Either fix it, or mark it known_failure with a reason. - print( - "\n refusing to update the baseline: " - f"{card.runs - card.passed} run(s) failed and are not marked known_failure" - ) - return 1 - save_baseline(card) - print(f" baseline updated for {card.label}") - return 0 - - comparison = compare(card, load_baseline()) - if comparison.notes: + print(f"\n{'─' * 72}") + print(format_scorecard(card)) + for name in card.known_failures: + reason = next(r.known_failure for r in cell_records if r.scenario == name) + print(f" known: {name} — {reason}") + + if args.update_baseline: + if card.pass_rate < 1.0: + # Saving here would record the failure as the accepted status quo + # and disarm its gate. Either fix it, or mark it known_failure. + print( + "\n refusing to update the baseline: " + f"{card.runs - card.passed} run(s) failed and are not marked known_failure" + ) + exit_code = 1 + continue + save_baseline(card) + print(f" baseline updated for {card.label}") + continue + + comparison = compare(card, baseline) for line in comparison.notes: print(f"\n note: {line}") - if comparison.improvements: - print("\n improvements vs baseline:") - for line in comparison.improvements: - print(f" + {line}") - if comparison.regressions: - print("\n REGRESSIONS vs baseline:") - for line in comparison.regressions: - print(f" - {line}") - - failed_expectations = card.pass_rate < 1.0 - gated = comparison.regressions and not args.no_gate - return 1 if (failed_expectations or gated) else 0 + if comparison.improvements: + print("\n improvements vs baseline:") + for line in comparison.improvements: + print(f" + {line}") + if comparison.regressions: + print("\n REGRESSIONS vs baseline:") + for line in comparison.regressions: + print(f" - {line}") + if card.pass_rate < 1.0 or (comparison.regressions and not args.no_gate): + exit_code = 1 + + if len(cards) > 1: + print(f"\n{'─' * 72}") + print(format_grid(cards, records)) + + flaky = cross_cell_flaky(records) + if flaky: + print("\n FLAKY (passed some repeats, not others):") + for line in flaky: + print(f" ~ {line}") + + print(f"\n elapsed: {time.monotonic() - started:.0f}s results: {path}") + return exit_code if __name__ == "__main__": diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 08b0cc1a..9f81aa65 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -318,7 +318,7 @@ async def drive() -> None: result.failures = [ message - for expectation in scenario.expectations_for(config.detector) + for expectation in scenario.expectations_for(config.detector, config.stt) if (message := expectation.check(result, scenario)) is not None ] return result diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 49b7791c..cff35e9d 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -17,7 +17,7 @@ import re from dataclasses import dataclass, field from difflib import SequenceMatcher -from typing import TYPE_CHECKING, Protocol +from typing import TYPE_CHECKING, Any, Protocol if TYPE_CHECKING: from harness import RunResult @@ -114,14 +114,53 @@ def fluent(*parts: str | float) -> list[Step]: # --------------------------------------------------------------------------- +_DIGIT_WORDS = { + "0": "zero", "1": "one", "2": "two", "3": "three", "4": "four", + "5": "five", "6": "six", "7": "seven", "8": "eight", "9": "nine", +} # fmt: skip + + +def _spell_digits(match: re.Match[str]) -> str: + return " ".join(_DIGIT_WORDS[d] for d in match.group()) + + def normalize(text: str) -> str: - return re.sub(r"\s+", " ", re.sub(r"[^\w\s]", "", text.lower())).strip() + """Lowercase, strip punctuation, and render digit runs as spoken words. + + The digit pass exists because providers disagree about a spoken digit string + with no bearing on turn-taking: Flux writes "four four seven two nine one" + and Nova writes "447291" for the same audio. Without it, `banking_digits` + fails in seven of twelve cells having committed exactly one turn in all + twelve — a pure formatting difference reported as a turn-taking defect. + + Digits are spelled out one by one rather than parsed as numbers, matching how + an account number is read aloud. "30 days" would normalize to "three zero + days", which is wrong, but nothing in the suite says a number that way. + """ + spelled = re.sub(r"\d+", _spell_digits, text.lower()) + return re.sub(r"\s+", " ", re.sub(r"[^\w\s]", "", spelled)).strip() def similarity(a: str, b: str) -> float: return SequenceMatcher(None, normalize(a), normalize(b)).ratio() +def best_window(haystack: str, needle: str) -> float: + """Similarity between ``needle`` and the closest same-length word window of ``haystack``. + + Whole-string similarity cannot see a dropped fragment inside a long utterance; + this can, because a missing part matches no window. + """ + hay, ned = normalize(haystack).split(), normalize(needle).split() + if not ned: + return 1.0 + if not hay: + return 0.0 + joined = " ".join(ned) + windows = (" ".join(hay[i : i + len(ned)]) for i in range(max(1, len(hay) - len(ned) + 1))) + return max(SequenceMatcher(None, joined, w).ratio() for w in windows) + + # --------------------------------------------------------------------------- # Expectations # --------------------------------------------------------------------------- @@ -158,12 +197,43 @@ class Merged: def check(self, result: RunResult, scenario: Scenario) -> str | None: if len(result.committed) != 1: return f"expected a single merged turn, got {len(result.committed)}: {result.committed}" + # Whole-string similarity alone lets a dropped fragment through: ElevenLabs + # committed coding_double_pause without "inside a test" and still scored 0.84 + # against the full sentence, so the scenario reported a clean merge on a third + # of the utterance being lost. A merge that loses a part is not a merge. + if (fault := AllPartsHeard().check(result, scenario)) is not None: + return fault score = similarity(self.text, result.committed[0]) if score < self.min_similarity: return f"merged text similarity {score:.2f} < {self.min_similarity}: {result.committed[0]!r}" return None +@dataclass(frozen=True) +class ContentPreserved: + """Everything spoken reached the agent, across however many turns it took. + + The turn-count-agnostic counterpart to :class:`Merged`. Use it when *whether* + an utterance splits is a defensible product choice but losing half of it is + not — at a long pause, holding and splitting are both reasonable, and a + scenario that demands one of them is asserting a policy it cannot justify. + This still catches the failure that actually hurts: ElevenLabs committing + "I'd like to order a large" and silently dropping the pizza. + """ + + min_similarity: float = 0.85 + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + if (fault := AllPartsHeard().check(result, scenario)) is not None: + return fault + spoken = " ".join(scenario.texts()) + heard = " ".join(result.committed) + score = similarity(spoken, heard) + if score < self.min_similarity: + return f"content similarity {score:.2f} < {self.min_similarity}: {heard!r} vs {spoken!r}" + return None + + @dataclass(frozen=True) class NoGhostTurns: """Every committed turn resembles something the script actually said. @@ -185,6 +255,29 @@ def check(self, result: RunResult, scenario: Scenario) -> str | None: return None +@dataclass(frozen=True) +class AllPartsHeard: + """Every scripted fragment reached the agent, wherever the turns fell. + + Similarity over a whole utterance is blind to a dropped tail, and the longer + the utterance the blinder it gets. ElevenLabs committed `coding_double_pause` + as "The build fails when I import the module" — "inside a test" simply gone — + and that still scores 0.84 against the full sentence, clearing the 0.8 bar on + `Merged`. The scenario reported a clean merge while a third of it was lost. + Matching each fragment against its best window catches the drop no matter how + much correct text surrounds it. + """ + + min_similarity: float = 0.75 + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + heard = " ".join(result.committed) + missing = [t for t in scenario.texts() if best_window(heard, t) < self.min_similarity] + if missing: + return f"fragments never heard: {missing} — got {result.committed}" + return None + + @dataclass(frozen=True) class Interrupted: """Whether a barge-in cancelled the assistant. @@ -268,15 +361,16 @@ class Scenario: script: list[Step] expect: list[Expectation] expect_by_detector: dict[str, list[Expectation]] = field(default_factory=dict) - """Per-detector overrides. Necessary because the same observable behavior can - be correct for different reasons: Deepgram Flux merges a mid-thought pause - inside its own turn machine, while ``lexical`` merges it via Timbal's HOLD.""" + """Overrides keyed by ``"detector"``, ``"stt/detector"`` or ``"*"``, most + specific first. Necessary because the same observable behavior can be correct + for different reasons: Deepgram Flux merges a mid-thought pause inside its own + turn machine, while ``lexical`` merges it via Timbal's HOLD.""" detectors: frozenset[str] | None = None """Detectors this scenario is meaningful for (``None`` = all).""" quick: bool = False """Part of the representative ``--quick`` subset (one per domain, plus a barge-in).""" known_failure: dict[str, str] = field(default_factory=dict) - """Detector (or ``"*"``) -> why this cannot pass today. + """``"detector"`` / ``"stt/detector"`` / ``"*"`` -> why this cannot pass today. The scenario still runs and still reports, but it does not gate, and its *desired* expectations stay in the file rather than being rewritten to match @@ -290,11 +384,31 @@ class Scenario: """ note: str = "" - def expectations_for(self, detector: str) -> list[Expectation]: - return self.expect_by_detector.get(detector, self.expect) + def _scoped(self, table: dict[str, Any], detector: str, stt: str | None) -> Any | None: + """Look up ``table`` by cell, then STT, then detector, then ``"*"``. + + Both overrides and known failures need this. A finding is usually specific + to one *cell*, not to a detector everywhere: `food_list_pause` merges under + `lexical` on Flux and splits under `lexical` on Nova, because on Flux the + provider merged it before any detector saw it. Keying by detector alone + would let a Flux observation silently excuse a Nova failure. + + The ``"deepgram-nova/*"`` rung exists because some failures are the STT's + alone and land identically under all four detectors — Nova committing a + "mm-hmm", ElevenLabs merging two finished sentences. Writing those out + per cell repeats one fact four times and hides that it is one fact. + """ + rungs = [f"{stt}/{detector}", f"{stt}/*"] if stt is not None else [] + for key in (*rungs, detector, "*"): + if (hit := table.get(key)) is not None: + return hit + return None + + def expectations_for(self, detector: str, stt: str | None = None) -> list[Expectation]: + return self._scoped(self.expect_by_detector, detector, stt) or self.expect - def known_failure_reason(self, detector: str) -> str | None: - return self.known_failure.get(detector) or self.known_failure.get("*") + def known_failure_reason(self, detector: str, stt: str | None = None) -> str | None: + return self._scoped(self.known_failure, detector, stt) def applies_to(self, detector: str) -> bool: return self.detectors is None or detector in self.detectors @@ -370,6 +484,25 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: # Under `provider` the session defers to the STT's endpointing entirely, so none of # Timbal's hold logic runs and whatever Flux decides stands. +# Under `provider` there is no Timbal hold to override the STT, so any pause Flux +# chooses to end its turn at becomes a split. Flux usually holds through these two +# and occasionally does not; a single run reads as a clean pass, and only --repeat +# shows the 2-in-3. Both fragments here end at the "--" Flux writes for a hesitation. +_FLUX_PROVIDER_SPLIT = ( + "Flux intermittently ends its turn at the pause rather than holding through it, and under " + "`provider` nothing in Timbal runs to override that — merged 2/3 at --repeat 3" +) + +# A spurious single-token "I" turn committed just after a correctly merged utterance. +# Long attributed to `banking_digits_pause` and assumed to be something about digit +# strings; `medical_filler_midway` reproduced it verbatim on ordinary words, so it is +# the Flux + `provider` path, not the content. Roughly one run in four to six, which is +# why it took a wider suite to catch twice. +_FLUX_PROVIDER_GHOST_I = ( + "Flux + `provider` intermittently commits a spurious single-token 'I' turn after the real " + "one; not specific to this scenario" +) + _PROVIDER_ENDPOINTING_FAILURE = ( "`provider` defers to Flux's endpointing, which splits here; `lexical` merges it " "correctly because Namo scores the fragment 0.00 incomplete" @@ -458,6 +591,99 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], note="Pairs with support_barge_in: same reply, later offset, measurably longer heard text.", ), + Scenario( + id="support_barge_in_instant", + domain="support", + replies=[_RETURN_POLICY_REPLY], + script=[ + Say("Tell me about your return policy."), + AwaitAssistantAudio(offset_ms=150), + Say("Actually, cancel that."), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), NoGhostTurns(), NoErrors()], + note=( + "Barge-in before the assistant is really speaking, racing playback start against " + "the interrupt. Deliberately asserts no HeardPrefix: at 150ms there may honestly " + "be nothing heard yet, and failing on that would be testing the expectation." + ), + ), + Scenario( + id="support_barge_in_one_word", + domain="support", + replies=[_RETURN_POLICY_REPLY], + script=[ + Say("Tell me about your return policy."), + AwaitAssistantAudio(offset_ms=900), + Say("Stop."), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), NoGhostTurns(), NoErrors()], + note=( + "The most important barge-in in voice UX and the one the code is built to ignore: " + "both HeuristicTurnDetector and ProviderTurnDetector drop partials shorter than " + "MIN_BARGE_IN_PARTIAL_WORDS (2) as mic blips, and 'Stop.' is one word. Asserts the " + "desired behavior rather than the implemented one — if this fails everywhere, the " + "gate is the finding." + ), + ), + Scenario( + id="support_pause_short", + domain="support", + replies=["Of course. What's the order number?"], + script=[ + *fluent("I need help with", 0.6, "my recent order."), + *_SETTLE, + ], + expect=[ + Merged("I need help with my recent order."), + NoGhostTurns(), + Interrupted(False), + NoErrors(), + ], + known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_SPLIT}, + intermittent=True, + note=( + "The floor of the pause family: 0.6s is shorter than any endpointer's silence " + "window, so every configuration should merge it. Exists to prove the harder pause " + "scenarios are measuring difficulty rather than a broken fixture — and it earns " + "that, merging in eleven of twelve cells. The exception is instructive: `provider` " + "on Flux splits even 0.6s about one run in three, so the floor is not the " + "detector's, it is whatever the STT decided." + ), + ), + Scenario( + id="support_trailing_conjunction", + domain="support", + replies=["I'm sorry to hear that. Let me check the tracking."], + script=[ + *fluent("I ordered a lamp last week and", 1.5, "it still hasn't arrived."), + *_SETTLE, + ], + expect=[ + Merged("I ordered a lamp last week and it still hasn't arrived."), + NoGhostTurns(), + NoErrors(), + ], + note=( + "A dangling coordinating conjunction is the strongest continuation cue in text, so " + "this is the pause case text EOU should get right without any help from prosody — " + "the complement to medical_hesitant_pause, where the fragment reads complete and " + "only prosody says otherwise." + ), + ), + Scenario( + id="support_silence_only", + domain="support", + replies=["Hello?"], + script=[Silence(4.0)], + expect=[UserTurns(0), NoAgentReply(), NoErrors()], + note=( + "Four seconds of nothing. No scenario previously asserted that an open mic with no " + "speech produces no turn, which is the purest form of the ghost-turn bug and the " + "one a VAD or watchdog misfire would cause." + ), + ), # -- food_ordering: enumerations, mid-list pauses -------------------------- Scenario( id="food_simple", @@ -496,24 +722,18 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *fluent("I'd like to order a large", 3.0, "pepperoni pizza please."), *_SETTLE, ], - expect=[UserTurns(2), NoGhostTurns(), NoErrors()], - expect_by_detector={ - # Observed, with the mechanism deliberately not asserted: under `lexical` and - # `local` this merges, and the event trace shows Flux never committing the - # first fragment at all — it streams partials through the whole 3s gap and - # emits one commit. So the merge happens inside Flux, not in Timbal's HOLD. - # Why the same cached audio splits under `provider` is still unexplained; - # `commit()` is a no-op for Flux, so it is not an obvious forced endpoint. - detector: [ - Merged("I'd like to order a large pepperoni pizza please."), - NoGhostTurns(), - NoErrors(), - ] - for detector in ("lexical", "local") - }, + expect=[ContentPreserved(), NoGhostTurns(), NoErrors()], note=( - "Splits under `provider`, merges under `lexical` and `local`, from byte-identical " - "cached audio. Consistent across runs but not yet explained — see the comment above." + "The one scenario whose desired outcome is genuinely ambiguous, so it asserts " + "content rather than turn count. At a 3.0s gap both answers are defensible — " + "holding costs 3s of dead air, splitting sends a fragment to the LLM — and the " + "suite has no basis for calling either wrong. Observed: Flux merges under " + "`lexical`/`local` and splits under `heuristic`/`provider`, Nova splits under all " + "four, ElevenLabs merges under `lexical`/`local`. Flux's merge is not Timbal's: " + "the trace shows Flux streaming partials through the whole gap and emitting one " + "commit, so no fragment ever reaches a detector. It previously demanded a merge " + "wherever one had been seen, which quietly turned observations into requirements " + "and failed Nova for behaving reasonably." ), ), Scenario( @@ -548,6 +768,68 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], expect=[UserTurns(2), Interrupted(True), HeardPrefix(), NoGhostTurns(), NoErrors()], ), + Scenario( + id="food_backchannel", + domain="food_ordering", + replies=[_MENU_REPLY], + script=[ + Say("Tell me what's on the menu today."), + AwaitAssistantAudio(offset_ms=1200), + Say("Mm-hmm."), + # No AwaitAssistantDone: the reply to turn 1 has already been generated and a + # correct run produces no second one, so waiting for one always times out. + Silence(3.0), + ], + expect=[UserTurns(1), Interrupted(False), NoGhostTurns(), NoErrors()], + known_failure={ + "deepgram-nova/*": "Nova transcribes the backchannel as 'Mhmm.' and commits it, " + "which cuts the assistant off; no detector sees anything to distinguish it from a " + "one-word barge-in", + "deepgram-flux/local": "same commit, intermittently — 2/3 at --repeat 3", + }, + intermittent=True, + note=( + "Listeners say 'mm-hmm' while you talk and do not mean stop. Nothing in the suite " + "distinguished a backchannel from a barge-in before this, and the two are " + "acoustically similar and semantically opposite. The split is by STT, not " + "detector: Flux and ElevenLabs swallow the sound, Nova transcribes it and all four " + "detectors then interrupt on it. Timbal has no notion of a backchannel, so on any " + "STT that transcribes one, an acknowledgement silences the assistant." + ), + ), + Scenario( + id="food_trailing_preposition", + domain="food_ordering", + replies=["Sure, I can deliver there."], + script=[ + *fluent("Can you deliver it to", 1.5, "the office on Main Street?"), + *_SETTLE, + ], + expect=[ + Merged("Can you deliver it to the office on Main Street?"), + NoGhostTurns(), + NoErrors(), + ], + note="A stranded preposition: syntactically incomplete, so text EOU should hold without prosody.", + ), + Scenario( + id="food_rapid_fire", + domain="food_ordering", + replies=["Two coffees, got it."], + script=[ + Say("I'll have a coffee."), + Silence(0.9), + Say("Actually, make it two."), + *_SETTLE, + ], + expect=[UserTurns(2), NoGhostTurns(), NoErrors()], + note=( + "The inverse of every pause scenario: two genuinely finished sentences separated by " + "a short gap, which must *not* merge. The suite is full of cases punishing a split " + "and had none punishing a merge, so a detector could have scored well by simply " + "holding everything." + ), + ), # -- medical_intake: hesitation-heavy ------------------------------------- Scenario( id="medical_simple", @@ -595,6 +877,90 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], expect=[UserTurns(2), Interrupted(True), HeardPrefix(), NoGhostTurns(), NoErrors()], ), + Scenario( + id="medical_barge_in_twice", + domain="medical_intake", + replies=[_FEVER_REPLY], + script=[ + Say("What should I do about a fever?"), + AwaitAssistantAudio(offset_ms=600), + Say("Wait, hold on."), + AwaitAssistantAudio(offset_ms=600), + Say("Okay, never mind."), + *_SETTLE, + ], + expect=[UserTurns(3), Interrupted(True), NoGhostTurns(), NoErrors()], + note=( + "Two interruptions in one session. Every other barge-in scenario stops after the " + "first, so nothing checked that the session recovers enough to be interrupted " + "again — a stuck playback or un-cleared interrupt flag would pass all of them." + ), + ), + Scenario( + id="medical_self_correction", + domain="medical_intake", + replies=["Noted, the white one."], + script=[ + *fluent("I take the blue pill, no wait,", 1.2, "the white one."), + *_SETTLE, + ], + expect=[ + Merged("I take the blue pill, no wait, the white one.", min_similarity=0.8), + NoGhostTurns(min_similarity=0.5), + NoErrors(), + ], + known_failure={"deepgram-flux/*": _TRAILING_MODIFIER_FAILURE}, + note=( + "Self-repair mid-utterance. 'No wait,' is a complete clause boundary that reads " + "finished to text EOU while guaranteeing more speech follows — and committing here " + "sends the LLM the retracted answer, which is worse than a split usually is. Fails " + "0/3 in every Flux cell and passes on nova/lexical and three ElevenLabs cells, so " + "the ceiling is the STT's segmentation rather than the detector's judgement." + ), + ), + Scenario( + id="medical_filler_midway", + domain="medical_intake", + replies=["Thanks. Anything else?"], + script=[ + *fluent("The pain is, um,", 1.3, "mostly at night."), + *_SETTLE, + ], + expect=[ + Merged("The pain is, um, mostly at night.", min_similarity=0.8), + NoGhostTurns(min_similarity=0.5), + NoErrors(), + ], + known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I}, + intermittent=True, + note=( + "A filler immediately before the gap, which is where hedges actually occur in " + "speech. medical_hesitation covers a bare 'Um...' at idle; this covers one " + "mid-sentence, where the hedge logic has to hold rather than suppress. It merges " + "the pause correctly everywhere and is marked only for the ghost 'I' — which it " + "was the first scenario other than banking_digits_pause to produce, retiring the " + "theory that the ghost had anything to do with digits." + ), + ), + Scenario( + id="medical_long_utterance", + domain="medical_intake", + replies=["That's helpful, thank you."], + script=[ + Say( + "I've been having headaches every morning for about two weeks and they " + "usually fade after breakfast but yesterday it lasted the whole day and " + "I felt dizzy whenever I stood up too quickly." + ), + *_SETTLE, + ], + expect=[UserTurns(1), ContentPreserved(min_similarity=0.8), NoGhostTurns(), NoErrors()], + note=( + "Twelve seconds of unbroken speech with several clause boundaries an endpointer " + "could mistake for an ending. The longest utterance in the suite by a wide margin; " + "everything else is short enough that a premature commit has nowhere to happen." + ), + ), # -- banking: digit strings and short confirmations ------------------------ Scenario( id="banking_digits", @@ -620,14 +986,15 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(min_similarity=0.4), NoErrors(), ], - known_failure={ - "provider": "Flux splits the digit string and commits a spurious single-token turn" - }, + known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I}, + intermittent=True, note=( "The hardest merge in the suite: a digit string broken across a pause, with no " "words to hint continuation. `lexical` and `local` merge it once the fragment " - "carries mid-sentence prosody; `provider` still splits and emits the one genuine " - "ghost turn the suite reproduces." + "carries mid-sentence prosody. `provider` mostly merges it too, but drops to a " + "split plus a ghost 'I' about one run in six, visible only under --repeat. That " + "ghost was assumed to be about digit strings until medical_filler_midway produced " + "the identical turn on ordinary words." ), ), Scenario( @@ -657,6 +1024,44 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: detectors=_FILLER_DETECTORS, note=_FILLER_NOTE, ), + Scenario( + id="banking_short_reject", + domain="banking", + replies=["Understood, I've cancelled it."], + script=[Say("No."), *_SETTLE], + expect=[UserTurns(1), NoGhostTurns(min_similarity=0.3), Interrupted(False), NoErrors()], + note=( + "The shortest possible real turn. Pairs with banking_confirmation, which is " + "intermittent for exactly this reason: ElevenLabs has been seen transcribing " + "one-word answers as partials that never commit, hanging the session outright. A " + "'No.' that goes unheard is a worse failure than a split." + ), + ), + Scenario( + id="banking_correction", + domain="banking", + replies=["Transferring to account four four eight."], + script=[ + *fluent("Send it to account four four seven, sorry,", 1.3, "four four eight."), + *_SETTLE, + ], + expect=[ + Merged("Send it to account four four seven, sorry, four four eight.", min_similarity=0.75), + NoGhostTurns(min_similarity=0.4), + NoErrors(), + ], + known_failure={ + "deepgram-flux/local": _TRAILING_MODIFIER_FAILURE, + "deepgram-flux/provider": _TRAILING_MODIFIER_FAILURE, + }, + note=( + "Self-correction on a digit string: no lexical context, and committing early sends " + "the LLM the wrong account number rather than merely a fragment. The one scenario " + "where a split has a concrete, wrong consequence — the agent acts on 447 when the " + "caller said 448. `lexical` merges it 3/3 on Flux where `local` and `provider` " + "never do, the clearest case in the suite of Namo beating the audio EOU outright." + ), + ), # -- coding_help: technical tokens --------------------------------------- Scenario( id="coding_simple", @@ -680,6 +1085,13 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(min_similarity=0.5), NoErrors(), ], + known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_SPLIT}, + intermittent=True, + note=( + "Baselined as a clean pass until --repeat 3 caught `provider` splitting it once in " + "three. Nothing changed in the product; the suite had only ever run it once per " + "cell. A worthwhile reminder that a green single run is weak evidence." + ), ), Scenario( id="coding_barge_in", @@ -693,6 +1105,74 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], expect=[UserTurns(2), Interrupted(True), HeardPrefix(), NoGhostTurns(), NoErrors()], ), + Scenario( + id="coding_barge_in_echo", + domain="coding_help", + replies=[_IMPORTS_REPLY], + script=[ + Say("Explain how Python handles imports."), + AwaitAssistantAudio(offset_ms=1400), + Say("Sorry, the module cache?"), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(True), NoGhostTurns(min_similarity=0.5), NoErrors()], + note=( + "A real interruption made of words the assistant is in the middle of saying, which " + "is what asking someone to repeat themselves sounds like. `_likely_stt_echo` " + "suppresses partials resembling the assistant's own text to survive a leaky AEC, " + "and cannot tell this apart from the echo it exists to drop. Measures that " + "suppressor's false-positive rate on genuine speech." + ), + ), + Scenario( + id="coding_double_pause", + domain="coding_help", + replies=["Sounds like an import cycle. Can you share the traceback?"], + script=[ + *fluent("The build fails when I", 1.2, "import the module", 1.2, "inside a test."), + *_SETTLE, + ], + expect=[ + Merged("The build fails when I import the module inside a test.", min_similarity=0.8), + NoGhostTurns(min_similarity=0.5), + NoErrors(), + ], + known_failure={ + "deepgram-flux/*": "holds through the first gap and splits at the second; the " + "fragment it commits reads as a finished sentence, so nothing argues for holding" + }, + intermittent=True, + note=( + "Two gaps in one sentence, and the first is the one that gets held: every Flux cell " + "merges 'The build fails when I' with 'import the module' and then commits, leaving " + "'inside a test' as its own turn. A hold that fires once and latches would look " + "identical, which is why one-gap scenarios could not have found this. ElevenLabs " + "merges all three — but see AllPartsHeard: it used to drop 'inside a test' entirely " + "and still score 0.84 similarity, and this scenario is what exposed that." + ), + ), + Scenario( + id="coding_followup_after_reply", + domain="coding_help", + replies=["A segfault means bad memory access."], + script=[ + Say("What does a segmentation fault mean?"), + AwaitCommit(), + AwaitAssistantDone(), + # AwaitAssistantDone fires when generation ends, not when playback drains, so + # speaking here would barge in on the tail. This waits out a ~2.5s reply. + Silence(5.0), + Say("And how do I debug it?"), + *_SETTLE, + ], + expect=[UserTurns(2), Interrupted(False), NoGhostTurns(), NoErrors()], + note=( + "A second turn taken after the assistant has finished speaking, uninterrupted. " + "This is a regression test for a bug we shipped: STT not resuming once the " + "assistant stopped, so the follow-up was never heard. Every other multi-turn " + "scenario barges in, which exercises the opposite path and would keep passing." + ), + ), ] diff --git a/benchmarks/voice/score.py b/benchmarks/voice/score.py index 089a940d..c46e2827 100644 --- a/benchmarks/voice/score.py +++ b/benchmarks/voice/score.py @@ -64,6 +64,9 @@ class RunRecord: known_failure: str = "" """Non-empty when this scenario is expected to fail for this detector.""" intermittent: bool = False + jobs: int = 1 + """Concurrency this run was measured under. Latency is only comparable at equal + concurrency, so it is recorded per run rather than inferred later.""" @property def xfail(self) -> bool: @@ -87,7 +90,7 @@ def count_ghost_turns(result: RunResult, scenario: Scenario, min_similarity: flo return sum(1 for text in result.committed if not any(similarity(text, said) >= min_similarity for said in spoken)) -def record(scenario: Scenario, result: RunResult, repeat: int = 0) -> RunRecord: +def record(scenario: Scenario, result: RunResult, repeat: int = 0, jobs: int = 1) -> RunRecord: return RunRecord( scenario=scenario.id, domain=scenario.domain, @@ -104,8 +107,9 @@ def record(scenario: Scenario, result: RunResult, repeat: int = 0) -> RunRecord: vad_endpointed=[m.vad_endpointed for m in result.metrics], errors=list(result.errors), wall_secs=round(result.wall_secs, 2), - known_failure=scenario.known_failure_reason(result.detector) or "", + known_failure=scenario.known_failure_reason(result.detector, result.stt) or "", intermittent=scenario.intermittent, + jobs=jobs, ) @@ -161,6 +165,9 @@ class Scorecard: known_failures: list[str] = field(default_factory=list) unexpected_passes: list[str] = field(default_factory=list) wall_secs: float = 0.0 + jobs: int = 1 + """Concurrency the cell ran at. Latency gating is suppressed unless this matches + the baseline's — contended runs measure the machine, not the change.""" def build_scorecard(records: list[RunRecord]) -> Scorecard: @@ -196,6 +203,7 @@ def build_scorecard(records: list[RunRecord]) -> Scorecard: known_failures=sorted({r.scenario for r in records if r.xfail}), unexpected_passes=sorted({r.scenario for r in records if r.xpass}), wall_secs=round(sum(r.wall_secs for r in records), 1), + jobs=max(r.jobs for r in records), ) @@ -225,6 +233,81 @@ def format_scorecard(card: Scorecard) -> str: return "\n".join(lines) +# --------------------------------------------------------------------------- +# Matrix +# --------------------------------------------------------------------------- + +# Grid glyphs. Deliberately distinguishes "failed" from "expected to fail": a cell +# full of x is a documented limitation, a single ✗ is a regression. +_PASS, _FAIL, _XFAIL, _XPASS, _FLAKY, _ABSENT = "✓", "✗", "x", "!", "~", "·" + + +def format_grid(cards: list[Scorecard], records: list[RunRecord]) -> str: + """Scenario × cell grid — the question the matrix exists to answer. + + Reading down a column compares scenarios within one configuration; reading + across a row shows which configurations handle a given situation, which is the + only way to tell a Timbal bug from a provider quirk. + """ + labels = [c.label for c in cards] + by_cell: dict[str, dict[str, list[RunRecord]]] = {label: {} for label in labels} + for r in records: + cell = by_cell.get(f"{r.stt}/{r.detector}") + if cell is not None: + cell.setdefault(r.scenario, []).append(r) + + scenarios = sorted({r.scenario for r in records}) + width = max((len(s) for s in scenarios), default=0) + columns = [str(i + 1) for i in range(len(labels))] + + def glyph(runs: list[RunRecord]) -> str: + if not runs: + return _ABSENT + rate = sum(r.passed for r in runs) / len(runs) + if runs[0].xfail: + return _XPASS if all(r.xpass for r in runs) else _XFAIL + if rate == 1.0: + return _PASS + return _FAIL if rate == 0.0 else _FLAKY + + lines = ["", "matrix (rows: scenarios, columns: cells)", ""] + lines.append(f" {'':<{width}} " + " ".join(f"{c:>3}" for c in columns)) + for name in scenarios: + row = " ".join(f"{glyph(by_cell[label].get(name, [])):>3}" for label in labels) + lines.append(f" {name:<{width}} {row}") + + lines.append("") + for i, card in enumerate(cards): + rate = f"{card.passed}/{card.runs}" + p50 = f"{card.latency_p50:.0f}ms" if card.latency_p50 is not None else "-" + lines.append(f" {i + 1:>3} {card.label:<28} {rate:>7} p50 {p50:>7}") + lines.append("") + lines.append( + f" {_PASS} pass {_FAIL} FAIL {_XFAIL} known failure {_XPASS} XPASS {_FLAKY} flaky {_ABSENT} not run" + ) + return "\n".join(lines) + + +def cross_cell_flaky(records: list[RunRecord]) -> list[str]: + """Scenarios that are flaky *within* at least one cell. + + Deliberately not "differs across cells" — that is the matrix working as + intended, since detectors are supposed to behave differently. Flakiness inside + a single cell is the one that means a race. + """ + by_cell_scenario: dict[tuple[str, str], list[RunRecord]] = {} + for r in records: + by_cell_scenario.setdefault((f"{r.stt}/{r.detector}", r.scenario), []).append(r) + flaky = set() + for (label, scenario), runs in by_cell_scenario.items(): + if len(runs) < 2: + continue + rate = sum(r.passed for r in runs) / len(runs) + if 0.0 < rate < 1.0: + flaky.add(f"{scenario} [{label}] {sum(r.passed for r in runs)}/{len(runs)}") + return sorted(flaky) + + # --------------------------------------------------------------------------- # Baseline + gating # --------------------------------------------------------------------------- @@ -287,6 +370,15 @@ def compare(card: Scorecard, baseline: dict[str, dict]) -> Comparison: if before_p50 and card.latency_p50: moved = card.latency_p50 / before_p50 delta = f"eou→audio p50 {before_p50:.0f}ms → {card.latency_p50:.0f}ms" + # Concurrent runs share CPU with each other's ONNX inference, so their + # latency measures the machine's load as much as the code's. Comparing + # across different --jobs would gate on scheduling noise. + before_jobs = previous.get("jobs", 1) + if card.jobs != before_jobs: + out.notes.append( + f"{delta} — not gated, measured at --jobs {card.jobs} against a --jobs {before_jobs} baseline" + ) + return out enough = min(card.latency_samples, previous.get("latency_samples", 0)) >= MIN_LATENCY_SAMPLES if moved > LATENCY_REGRESSION_RATIO: worse = f"{delta} (>{(LATENCY_REGRESSION_RATIO - 1) * 100:.0f}% worse)" diff --git a/benchmarks/voice/synth.py b/benchmarks/voice/synth.py index befaaf4d..111c0899 100644 --- a/benchmarks/voice/synth.py +++ b/benchmarks/voice/synth.py @@ -198,9 +198,7 @@ def slice_fluent(pcm: bytes, char_end_times: Sequence[float], parts: Sequence[st return slices -async def _synthesize_aligned( - utterance: str, voice_id: str, model: str -) -> tuple[bytes, list[float]]: +async def _synthesize_aligned(utterance: str, voice_id: str, model: str) -> tuple[bytes, list[float]]: """Whole-utterance PCM plus per-character end times, cached on disk. Uses the REST ``with-timestamps`` endpoint; the streaming websocket used for From 706555498848db8b291a9d1befead4d1bcf82910 Mon Sep 17 00:00:00 2001 From: berges99 Date: Sat, 25 Jul 2026 19:29:02 +0200 Subject: [PATCH 04/30] feat(bench): measure dead air, the metric hold policy was invisible to eou->audio starts counting at the accepted commit, so every second a hold spends deciding costs nothing measurable, and pass/fail only ever saw whether the turn eventually merged. Between them the two metrics could not see hold policy at all. That blindness had teeth. Disabling the text-complete hold tier reads as 11 scenario-cells fixed and zero regressions, taking every local cell to 95% - Flux 89->95, Nova 79->95, ElevenLabs 87->95 - and on that evidence it looks like an obvious win. Timing speech end to commit says otherwise: it fires on 21% of scenario-cells, and the cost lands on cases that were already correct. Six barge-in cells take +2.6s before the assistant answers an ordinary question, three closers take +2.6s, and medical_long_utterance is counted as a fix while taking +8.2s. The tier stays. So: record speech end -> turn accepted per commit, add MaxDeadAir, and gate dead-air p50 per cell alongside latency with the same ratio, sample floor and --jobs-mismatch suppression. The two gates share _compare_timing because the old latency block returned early on a jobs mismatch and would have skipped dead air entirely - the same shape of bug as the one this commit is about. support_closer swaps its "deliberately carries no MaxLatency" note for MaxDeadAir(3500). It sits at 1.9s median and 2.8s worst today and lands near 4.5s with the tier removed, so the ceiling catches that specific regression. It is a tripwire on six samples, not a tight bound; the per-cell gate is the real instrument. Measured across the three gated cells: p50 560-699ms, p95 1.6-2.2s, n~50 each, all still 100%. Not gating yet - baseline.json has no dead_air_p50 entries until it is regenerated serially, so _compare_timing returns early for now. One thing this immediately surfaced and did not explain: dead air reaches 7.5s on banking_digits and banking_digits_pause, a plain account number with no hold involved, which is longer than anything the tier does. No product code changes. The tier experiment above was run by temporarily setting TEXT_COMPLETE_HOLD_TIMEOUT_SECS to 3.0 and reverted. --- benchmarks/voice/harness.py | 22 +++++++++- benchmarks/voice/scenario.py | 43 +++++++++++++++++-- benchmarks/voice/score.py | 80 ++++++++++++++++++++++++++---------- 3 files changed, 118 insertions(+), 27 deletions(-) diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 9f81aa65..15e2e542 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -98,6 +98,16 @@ class RunResult: audio_bytes: int = 0 wall_secs: float = 0.0 failures: list[str] = field(default_factory=list) + # Wall time from the user falling silent to the turn being accepted — the + # dead air a caller actually sits through, and the half of the picture + # `latencies_ms` cannot see. `eou→first audio` starts at the *accepted* + # commit, so every second a hold spends deciding is invisible to it. That + # blindness let a tier-removal experiment read as 11 fixes and 0 + # regressions while adding 2.6s to six barge-in cells. + dead_air_ms: list[float] = field(default_factory=list) + # Monotonic timestamp of the most recent speech end, consumed by the next + # commit. Not an output; internal to the measurement. + speech_ended_at: float | None = None @property def passed(self) -> bool: @@ -266,6 +276,10 @@ async def drive() -> None: replies_at_say = len(result.replies_spoken) feeder.push(clips[step.clip_key]) await feeder.drain() + # drain() returns once the last frame is pushed, so this is the + # instant the speaker fell silent. A later part of the same + # fluent utterance overwrites it, leaving the final speech end. + result.speech_ended_at = time.monotonic() elif isinstance(step, Silence): emit("silence", f"{step.secs:.1f}s") await asyncio.sleep(step.secs) @@ -343,7 +357,13 @@ def _observe( elif isinstance(event, TranscriptPartial): emit("partial", f'"{event.text}"') elif isinstance(event, TranscriptCommitted): - emit("committed", f'"{event.text}"{" (replace)" if event.replace else ""}') + detail = f'"{event.text}"{" (replace)" if event.replace else ""}' + if result.speech_ended_at is not None: + dead_air = (time.monotonic() - result.speech_ended_at) * 1000 + result.dead_air_ms.append(dead_air) + result.speech_ended_at = None + detail += f" dead air {dead_air:.0f}ms" + emit("committed", detail) if event.replace and result.committed: result.committed[-1] = event.text else: diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index cff35e9d..f247695f 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -327,7 +327,12 @@ def check(self, result: RunResult, scenario: Scenario) -> str | None: @dataclass(frozen=True) class MaxLatency: - """Every turn's ``eou_to_first_audio_ms`` stayed under a ceiling.""" + """Every turn's ``eou_to_first_audio_ms`` stayed under a ceiling. + + Measures the *pipeline* after a turn is accepted. It cannot see a hold, + because its clock starts at the accepted commit — use :class:`MaxDeadAir` + for anything that changes turn-taking timing. + """ ms: float @@ -338,6 +343,32 @@ def check(self, result: RunResult, scenario: Scenario) -> str | None: return None +@dataclass(frozen=True) +class MaxDeadAir: + """Time from the user falling silent to the turn being accepted. + + The assertion that makes hold policy falsifiable. Every other metric here is + blind to it: `eou→audio` starts at the accepted commit, so a hold that sits + for three seconds before committing costs nothing measurable, and pass/fail + only ever saw whether the turn eventually merged. + + That blindness had teeth. Disabling the text-complete hold tier reads as 11 + scenario-cells fixed and zero regressions, and on that evidence it looks + like an obvious win — while adding 2.6s before the assistant answers an + ordinary question in six barge-in cells, 2.6s to three closers, and 8.2s to + a long run-on it "fixed". Use this on any scenario where the speaker has + genuinely finished, so buying a merge with dead air has to be declared. + """ + + ms: float + + def check(self, result: RunResult, scenario: Scenario) -> str | None: + over = [v for v in result.dead_air_ms if v > self.ms] + if over: + return f"dead air over {self.ms}ms: {[round(v) for v in over]}" + return None + + @dataclass(frozen=True) class NoErrors: def check(self, result: RunResult, scenario: Scenario) -> str | None: @@ -547,7 +578,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: domain="support", replies=["Happy to help. Have a good day."], script=[Say("That's all."), *_SETTLE], - expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), MaxDeadAir(3500), NoErrors()], note=( "The case the text-complete hold tier exists for, and the only one in the suite: " "Smart Turn under-scores this closer (0.115 — 13 of 14 closers measured score " @@ -555,8 +586,12 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "is armed on an utterance that is actually over. Disabling the tier costs 2.7s of " "dead air here (speech end to reply: 0.91s with it, 3.59s without), which is why " "the tier survives even though it is what splits medical_hesitant_pause. " - "Deliberately carries no MaxLatency: eou→audio is measured from the *accepted* " - "commit, so it reads ~200ms either way and cannot see the hold." + "Carries MaxDeadAir rather than MaxLatency, because eou→audio is measured from " + "the *accepted* commit and reads ~200ms whether the hold ran or not. Dead air " + "sits at 1.9s median / 2.8s worst with the tier; removing it puts this at ~4.5s, " + "which is what the 3500ms ceiling is placed to catch. It is a tripwire on a " + "6-sample distribution, not a tight bound — the per-cell dead-air gate in " + "score.py is the real instrument." ), ), Scenario( diff --git a/benchmarks/voice/score.py b/benchmarks/voice/score.py index c46e2827..04cc1c78 100644 --- a/benchmarks/voice/score.py +++ b/benchmarks/voice/score.py @@ -58,6 +58,7 @@ class RunRecord: interrupted: bool heard_chars: int | None latencies_ms: list[float] + dead_air_ms: list[float] vad_endpointed: list[bool] errors: list[str] wall_secs: float @@ -104,6 +105,7 @@ def record(scenario: Scenario, result: RunResult, repeat: int = 0, jobs: int = 1 interrupted=result.interrupted, heard_chars=None if result.heard_text is None else len(result.heard_text), latencies_ms=[round(v, 1) for v in result.latencies_ms], + dead_air_ms=[round(v, 1) for v in result.dead_air_ms], vad_endpointed=[m.vad_endpointed for m in result.metrics], errors=list(result.errors), wall_secs=round(result.wall_secs, 2), @@ -158,6 +160,12 @@ class Scorecard: latency_min: float | None = None latency_max: float | None = None latency_samples: int = 0 + # Speech end -> turn accepted. Gated alongside latency because it is the only + # metric that can see a hold: `eou→audio` starts counting at the accepted + # commit, so hold policy is invisible to it by construction. + dead_air_p50: float | None = None + dead_air_p95: float | None = None + dead_air_samples: int = 0 per_scenario: dict[str, float] = field(default_factory=dict) """Gated scenario id -> pass rate across repeats. Known failures are excluded, so marking one cannot quietly bake broken behavior into the baseline.""" @@ -182,6 +190,7 @@ def build_scorecard(records: list[RunRecord]) -> Scorecard: per_scenario = {name: sum(r.passed for r in runs) / len(runs) for name, runs in by_scenario.items()} # Latency describes the stack, not an expectation, so known failures still count. latencies = [v for r in records for v in r.latencies_ms] + dead_air = [v for r in records for v in r.dead_air_ms] passed = sum(r.passed for r in gated) return Scorecard( @@ -198,6 +207,9 @@ def build_scorecard(records: list[RunRecord]) -> Scorecard: latency_min=min(latencies) if latencies else None, latency_max=max(latencies) if latencies else None, latency_samples=len(latencies), + dead_air_p50=percentile(dead_air, 0.5), + dead_air_p95=percentile(dead_air, 0.95), + dead_air_samples=len(dead_air), per_scenario=dict(sorted(per_scenario.items())), flaky=sorted(name for name, rate in per_scenario.items() if 0.0 < rate < 1.0), known_failures=sorted({r.scenario for r in records if r.xfail}), @@ -219,6 +231,12 @@ def format_scorecard(card: Scorecard) -> str: f"range {card.latency_min:.0f}-{card.latency_max:.0f}ms " f"n={card.latency_samples}{gated}" ) + if card.dead_air_p50 is not None: + gated = "" if card.dead_air_samples >= MIN_LATENCY_SAMPLES else " (ungated: too few samples)" + lines.append( + f" dead air: p50 {card.dead_air_p50:.0f}ms p95 {card.dead_air_p95:.0f}ms " + f"n={card.dead_air_samples}{gated} (speech end → turn accepted)" + ) failing = [name for name, rate in card.per_scenario.items() if rate < 1.0] if failing: lines.append(f" failing: {', '.join(failing)}") @@ -366,27 +384,45 @@ def compare(card: Scorecard, baseline: dict[str, dict]) -> Comparison: if card.ghost_turns > previous.get("ghost_turns", 0): out.regressions.append(f"ghost turns {previous.get('ghost_turns', 0)} → {card.ghost_turns}") - before_p50 = previous.get("latency_p50") - if before_p50 and card.latency_p50: - moved = card.latency_p50 / before_p50 - delta = f"eou→audio p50 {before_p50:.0f}ms → {card.latency_p50:.0f}ms" - # Concurrent runs share CPU with each other's ONNX inference, so their - # latency measures the machine's load as much as the code's. Comparing - # across different --jobs would gate on scheduling noise. - before_jobs = previous.get("jobs", 1) - if card.jobs != before_jobs: - out.notes.append( - f"{delta} — not gated, measured at --jobs {card.jobs} against a --jobs {before_jobs} baseline" - ) - return out - enough = min(card.latency_samples, previous.get("latency_samples", 0)) >= MIN_LATENCY_SAMPLES - if moved > LATENCY_REGRESSION_RATIO: - worse = f"{delta} (>{(LATENCY_REGRESSION_RATIO - 1) * 100:.0f}% worse)" - if enough: - out.regressions.append(worse) - else: - out.notes.append(f"{worse} — not gated, fewer than {MIN_LATENCY_SAMPLES} samples") - elif moved < 1 / LATENCY_REGRESSION_RATIO: - out.improvements.append(delta) + _compare_timing(out, card, previous, "latency", "eou→audio p50", card.latency_p50, card.latency_samples) + _compare_timing(out, card, previous, "dead_air", "dead air p50", card.dead_air_p50, card.dead_air_samples) return out + + +def _compare_timing( + out: Comparison, + card: Scorecard, + previous: dict, + key: str, + label: str, + now: float | None, + samples: int, +) -> None: + """Gate one timing percentile against its baseline entry. + + Both timings gate identically, but they answer different questions and a + change can move one without the other: removing the text-complete hold tier + left `eou→audio` flat — it starts at the accepted commit — while adding + 2.6s of dead air to six barge-in cells. + """ + before = previous.get(f"{key}_p50") + if not before or not now: + return + delta = f"{label} {before:.0f}ms → {now:.0f}ms" + # Concurrent runs share CPU with each other's ONNX inference, so their + # timings measure the machine's load as much as the code's. Comparing + # across different --jobs would gate on scheduling noise. + before_jobs = previous.get("jobs", 1) + if card.jobs != before_jobs: + out.notes.append(f"{delta} — not gated, measured at --jobs {card.jobs} against a --jobs {before_jobs} baseline") + return + moved = now / before + if moved > LATENCY_REGRESSION_RATIO: + worse = f"{delta} (>{(LATENCY_REGRESSION_RATIO - 1) * 100:.0f}% worse)" + if min(samples, previous.get(f"{key}_samples", 0)) >= MIN_LATENCY_SAMPLES: + out.regressions.append(worse) + else: + out.notes.append(f"{worse} — not gated, fewer than {MIN_LATENCY_SAMPLES} samples") + elif moved < 1 / LATENCY_REGRESSION_RATIO: + out.improvements.append(delta) From 8ee47a1b31f690375f72ba19c8e4b8f33a475fdf Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 12:17:08 +0200 Subject: [PATCH 05/30] style(voice): reflow to the configured 120-char line length MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Formatter pass over the voice module, no behaviour change. Verified by comparing the parsed AST of each file against HEAD: all five are identical, so the diff is line joining and one list exploding onto separate lines. Split out from the endpointing work in the same tree precisely because it is large and empty — 111 changed lines in eou.py alone, which read at a glance like someone had rewritten the dangling-token table. --- python/timbal/voice/deepgram.py | 4 +- python/timbal/voice/eou.py | 111 +++++++++++++++++++++++--- python/timbal/voice/namo.py | 10 +-- python/timbal/voice/realtime.py | 4 +- python/timbal/voice/turn_detection.py | 55 +++++++------ 5 files changed, 135 insertions(+), 49 deletions(-) diff --git a/python/timbal/voice/deepgram.py b/python/timbal/voice/deepgram.py index a852795f..8ae3a304 100644 --- a/python/timbal/voice/deepgram.py +++ b/python/timbal/voice/deepgram.py @@ -187,9 +187,7 @@ async def _receive_loop(self) -> None: # Deepgram closes normally after CloseStream; only surface abnormal # closures as errors so the session tears down loudly. if not self._stop.is_set() and e.rcvd is not None and e.rcvd.code not in (1000, 1001): - await self._queue.put( - TranscriptEvent(type="error", text=f"STT connection closed: {e}") - ) + await self._queue.put(TranscriptEvent(type="error", text=f"STT connection closed: {e}")) except Exception as e: logger.error("dg_stt_receive_error", error=str(e), exc_info=True) await self._queue.put(TranscriptEvent(type="error", text=f"STT receive error: {e}")) diff --git a/python/timbal/voice/eou.py b/python/timbal/voice/eou.py index 360b0221..9c18e5e4 100644 --- a/python/timbal/voice/eou.py +++ b/python/timbal/voice/eou.py @@ -81,16 +81,91 @@ async def predict_eou(self, text: str) -> float: _DANGLING_TOKENS = frozenset( { # English - "and", "or", "but", "so", "because", "if", "when", "while", "that", - "which", "who", "to", "of", "for", "with", "from", "in", "on", "at", - "by", "the", "a", "an", "my", "your", "our", "their", "his", "her", - "its", "i", "we", "you", "they", "it", "is", "are", "was", "were", - "um", "uh", "like", "then", "as", "than", "into", "about", "over", + "and", + "or", + "but", + "so", + "because", + "if", + "when", + "while", + "that", + "which", + "who", + "to", + "of", + "for", + "with", + "from", + "in", + "on", + "at", + "by", + "the", + "a", + "an", + "my", + "your", + "our", + "their", + "his", + "her", + "its", + "i", + "we", + "you", + "they", + "it", + "is", + "are", + "was", + "were", + "um", + "uh", + "like", + "then", + "as", + "than", + "into", + "about", + "over", # Spanish - "y", "e", "o", "u", "pero", "porque", "que", "si", "cuando", - "mientras", "de", "del", "para", "por", "con", "sin", "en", - "la", "el", "los", "las", "un", "una", "unos", "unas", "mi", "tu", - "su", "es", "está", "estoy", "eh", "este", "esto", "como", "más", + "y", + "e", + "o", + "u", + "pero", + "porque", + "que", + "si", + "cuando", + "mientras", + "de", + "del", + "para", + "por", + "con", + "sin", + "en", + "la", + "el", + "los", + "las", + "un", + "una", + "unos", + "unas", + "mi", + "tu", + "su", + "es", + "está", + "estoy", + "eh", + "este", + "esto", + "como", + "más", "muy", } ) @@ -102,8 +177,22 @@ async def predict_eou(self, text: str) -> float: # Namo-class text EOU behind the same :class:`TextEouPredictor` interface. _SHORT_HEDGES = frozenset( { - "uh", "um", "uhm", "hmm", "mm", "mhm", "mmhmm", "well", "so", "like", - "maybe", "perhaps", "idk", "pues", "este", "eh", + "uh", + "um", + "uhm", + "hmm", + "mm", + "mhm", + "mmhmm", + "well", + "so", + "like", + "maybe", + "perhaps", + "idk", + "pues", + "este", + "eh", } ) _PHRASE_HEDGES = frozenset( diff --git a/python/timbal/voice/namo.py b/python/timbal/voice/namo.py index d70c4d36..1d2f3720 100644 --- a/python/timbal/voice/namo.py +++ b/python/timbal/voice/namo.py @@ -120,9 +120,7 @@ def _prepare_text_for_namo(text: str) -> tuple[str, float | None]: @lru_cache(maxsize=4) -def _load_bundle( - repo_id: str, filename: str, cpu_count: int, max_length: int -) -> tuple[ort.InferenceSession, object]: +def _load_bundle(repo_id: str, filename: str, cpu_count: int, max_length: int) -> tuple[ort.InferenceSession, object]: """One (ort session, tokenizer) per repo — shared process-wide.""" path = _hf_download_cached_first(repo_id, filename) logger.debug("namo_loading_model", path=path, repo_id=repo_id) @@ -179,11 +177,7 @@ def __init__( model_path: str | None = None, cpu_count: int = 1, ) -> None: - self.repo_id = ( - repo_id - or os.environ.get("TIMBAL_NAMO_REPO_ID") - or DEFAULT_REPO_ID - ) + self.repo_id = repo_id or os.environ.get("TIMBAL_NAMO_REPO_ID") or DEFAULT_REPO_ID self.model_path = model_path self.cpu_count = cpu_count self.max_length = _MAX_LENGTH_BY_REPO.get(self.repo_id, _DEFAULT_MAX_LENGTH) diff --git a/python/timbal/voice/realtime.py b/python/timbal/voice/realtime.py index af9c6496..5341bb42 100644 --- a/python/timbal/voice/realtime.py +++ b/python/timbal/voice/realtime.py @@ -382,9 +382,7 @@ async def _handle_interruption(self, *, notify_model: bool) -> None: if self._turn_text or self._turn_audio_bytes: # S2S interleaves text and audio without segment boundaries: map the # heard position proportionally over the whole turn. - heard_text = map_played_bytes_to_text( - [(self._turn_text, self._turn_audio_bytes)], heard_bytes - ) + heard_text = map_played_bytes_to_text([(self._turn_text, self._turn_audio_bytes)], heard_bytes) if self._turn_active: if heard_text: self._transcript.append(TranscriptEntry(role="assistant", text=heard_text)) diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index 263fa3ab..e5759d96 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -184,10 +184,31 @@ def _is_garbage_commit(text: str) -> bool: # "no", "sí", "ok", "ya" must never match. _HESITATION_TOKENS = frozenset( { - "uh", "uhh", "uhhh", "um", "umm", "ummm", "uhm", "uhum", - "hm", "hmm", "hmmm", "mm", "mmm", "mhm", "mmhm", - "er", "erm", "eh", "ehh", "ehm", "em", - "ah", "ahh", "ahhh", "aah", + "uh", + "uhh", + "uhhh", + "um", + "umm", + "ummm", + "uhm", + "uhum", + "hm", + "hmm", + "hmmm", + "mm", + "mmm", + "mhm", + "mmhm", + "er", + "erm", + "eh", + "ehh", + "ehm", + "em", + "ah", + "ahh", + "ahhh", + "aah", } ) _HESITATION_WORD_RE = re.compile(r"[a-zà-öø-ÿ']+") @@ -335,10 +356,7 @@ async def on_partial(self, text: str, state: TurnState) -> PartialDecision: is_noise = _is_noise(text) is_hesitation = _is_hesitation_only(text) is_echo = _likely_stt_echo(text, state.assistant_text) if not is_noise else False - too_short = ( - len(text) < self.MIN_BARGE_IN_PARTIAL_CHARS - or len(text.split()) < self.MIN_BARGE_IN_PARTIAL_WORDS - ) + too_short = len(text) < self.MIN_BARGE_IN_PARTIAL_CHARS or len(text.split()) < self.MIN_BARGE_IN_PARTIAL_WORDS if not is_noise and not is_hesitation and not is_echo and not too_short: return PartialDecision.BARGE_IN logger.debug( @@ -426,9 +444,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: # utterance → not a VAD mid-phrase split. Ultra-early crumbs # are STT ghosts (live: "…killer." then "No." at +55ms); # anything later is a real short barge-in → NEW_TURN below. - if _looks_like_finished_utterance(state.active_user_text) and _looks_like_fresh_hold_utterance( - text - ): + if _looks_like_finished_utterance(state.active_user_text) and _looks_like_fresh_hold_utterance(text): words = _WORD_RE.findall(text) if ( state.seconds_since_last_commit < self.TRAILING_CRUMB_WINDOW_SECS @@ -688,9 +704,7 @@ def __init__( self.audio_eou = audio_eou if completion_threshold is not None: self.completion_threshold = completion_threshold - self.hold_timeout_secs = ( - hold_timeout_secs if hold_timeout_secs is not None else self.DEFAULT_HOLD_TIMEOUT_SECS - ) + self.hold_timeout_secs = hold_timeout_secs if hold_timeout_secs is not None else self.DEFAULT_HOLD_TIMEOUT_SECS self.text_complete_hold_timeout_secs = ( text_complete_hold_timeout_secs if text_complete_hold_timeout_secs is not None @@ -911,9 +925,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: action=CommitAction.HOLD, text=candidate, reason="audio_complete_text_incomplete", - hold_timeout_secs=min( - self.text_incomplete_hold_timeout_secs, self.hold_timeout_secs - ), + hold_timeout_secs=min(self.text_incomplete_hold_timeout_secs, self.hold_timeout_secs), ) return CommitDecision( action=CommitAction.NEW_TURN, @@ -926,10 +938,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: if ( state.active_user_text and state.assistant_active - and not ( - _looks_like_finished_utterance(state.active_user_text) - and _looks_like_fresh_hold_utterance(text) - ) + and not (_looks_like_finished_utterance(state.active_user_text) and _looks_like_fresh_hold_utterance(text)) ): combined = state.active_user_text.rstrip(", ") + " " + text return CommitDecision( @@ -1047,8 +1056,6 @@ def resolve_turn_detector(spec: Any = None) -> TurnDetector: if callable(spec): built = spec() if not isinstance(built, TurnDetector): - raise TypeError( - f"turn_detector factory must return a TurnDetector, got {type(built)!r}" - ) + raise TypeError(f"turn_detector factory must return a TurnDetector, got {type(built)!r}") return built raise TypeError(f"turn_detector must be str | TurnDetector | callable | None, got {type(spec)!r}") From 57efad1aac664b802c8951c737a87166498f3c00 Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 12:17:25 +0200 Subject: [PATCH 06/30] fix(voice): arm the commit fast path for text-only detectors MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The VAD endpointing fast path only armed when the turn detector exposed an audio EOU model. But its job is telling the STT to finalize, which has nothing to do with how the turn end was decided, so the coupling locked it away from the configuration that needs it most: a text-only detector on an STT that does not endpoint aggressively just waits. Measured on deepgram-nova/lexical, a spoken account number sat 7.5s from speech end to commit, against 750ms for the same audio under local. Flux hid it completely by endpointing itself. The audio score was also the sole driver of the delay, not just an arming precondition, so there was no "arm without a model" path to switch on. endpointing_delay only needs a P(complete), so the endpointer now sizes the delay from the text score when no audio score exists, and skips the incomplete-text bump in that mode to avoid pricing the same signal twice. Arming Silero also switches on three behaviours that read its speech history as evidence about the user — barge-in vetoing, hallucination vetoing, hold extension — all of which branch on `_endpointer is None` and take conservative defaults today. Those stay off unless an audio EOU exists (`_vad_evidence`). Silero being loaded is not a reason to start vetoing barge-ins on a detector that never has, and a latency fix should not change barge-in policy as a side effect. Measured: banking_digits on nova/lexical 7.5s -> 1.07s, 3/3. The three gated Flux cells hold at 100% with dead air slightly better in all three (725->663, 819->638, 550->526ms). Barge-in under lexical is 9/9 across all three backends. banking_digits_pause on nova/lexical now splits, which is the honest outcome: the old merge was the 7.5s stall swallowing a 1.4s gap, and that cell splits pauses 80% of the time anyway. Two harness corrections fell out. support_barge_in capped heard text at 80 chars, inside the harness's own 250ms ack resolution — runs landed at 82 and 85 with the interrupt woperfectly, reading as a barge-in regression on a change that had none; now 100. And food_backchannel was marked only for deepgram-flux/local until a re-baseline caught the same "Mhmm." commit under lexical, so it is scoped to deepgram-flux/* with the measured rate. The refuse-to-save-on-failure guard is what caught it, rather than a green baseline being written over a real failure. Baselines regenerated serially so dead air gates: p50 725/819/550ms at n~50 per cell, above the 20-sample floor. Adds sweep.py and HarnessConfig.detector_params so a parameter can be varied without editing product constants and re-running by hand — which is how the hold tier came to be measured at 0.35 and 3.0 and nowhere between. First result, 390 runs over the pause-merge family: merges go 58% -> 90% across that range while median dead air stays flat at 793-889ms, because the tier fires on a minority of turns and its cost is a tail effect (p95 2270 -> 3617ms). 1.2 scores 81% at p95 1944ms. Not applied. On the full 12-cell id 1.2 is +7 on the three local cells against +-2/cell run-to-run noise, and no value of the timeout moves medical_self_correction (50%) or banking_correction (33%) — the two trailing-modifier cases with real consequences. The knob is not the lever for those. Default stays 0.35. --- benchmarks/voice/README.md | 86 +++++++++++++-- benchmarks/voice/baseline.json | 47 +++++---- benchmarks/voice/harness.py | 39 ++++++- benchmarks/voice/scenario.py | 26 ++++- benchmarks/voice/sweep.py | 164 +++++++++++++++++++++++++++++ python/timbal/voice/endpointing.py | 44 ++++---- python/timbal/voice/session.py | 86 ++++++++++----- 7 files changed, 414 insertions(+), 78 deletions(-) create mode 100644 benchmarks/voice/sweep.py diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 76b1725d..a789b88b 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -81,10 +81,17 @@ Gating the tier on the audio score does not resolve it either. At the tier, clos score {0.115} and fragments {0.054, 0.376}: the fragments straddle the closer, so no threshold separates them. -**Careful with `eou→audio`: it is measured from the *accepted* commit, so it does -not include hold time.** A detector that holds for three seconds and then answers -in 200ms reports 200ms. Cross-detector latency comparisons in this README are only -meaningful where holds do not fire; where they do, read the event timeline instead. +**Two timings, and confusing them will mislead you.** `eou→audio` is measured +from the *accepted* commit, so it does not include hold time: a detector that +holds three seconds and then answers in 200ms reports 200ms. `dead air` is +speech end → turn accepted, and is the only metric that can see a hold. Both are +gated per cell against the baseline. A change can move one without the other — +removing the text-complete hold tier leaves `eou→audio` flat while adding 2.6s of +dead air to six barge-in cells. + +Use `MaxDeadAir` on any scenario where the speaker has genuinely finished, so +that buying a merge with silence has to be declared rather than slipping through +as a free win. **Flux's `end_of_turn_confidence` does not rescue it.** Across all 28 commits in a suite run, mid-thought fragments scored 0.690–0.920 and genuine turn ends @@ -272,6 +279,67 @@ are scoped to specific cells rather than blanket-marked, and eight are `intermittent` — but a suite that marks everything interesting gates nothing, and this is the point at which that stops being a theoretical concern. +### The suite could not see the cost of a hold + +`eou→audio` starts counting at the *accepted* commit, so every second a hold +spends deciding costs nothing measurable. Pass/fail only ever saw whether a turn +eventually merged. Between them, the two metrics were blind to turn-taking +timing — and that blindness nearly shipped a bad change. + +The text-complete hold tier shortens a hold to 0.35s when the audio model says +"incomplete" but the transcript reads finished. Disabling it looks like an +unambiguous win: **11 scenario-cells fixed, zero regressions**, every `local` +cell converging on 95% (Flux 89→95, Nova 79→95, ElevenLabs 87→95), including +`medical_hesitant_pause` on all three backends. + +Timing speech end to commit tells the other half. The tier fires on **21% of +scenario-cells**, and the cost lands almost entirely on cases that were already +correct: + +| scenario-cell | cost of removing the tier | was it failing before? | +|---|---:|---| +| `medical_barge_in`, `medical_barge_in_twice` (6 cells) | +2.6s | no — pure loss | +| `support_closer` (3 cells) | +2.6s | no — pure loss | +| `support_pause` (3 cells) | +2.4s | no — pure loss | +| `medical_long_utterance` (Nova) | **+8.2s** | counted as a *fix* | + +Six barge-in cells taking 2.6s longer to answer an ordinary question is not +visible anywhere in pass/fail, and an 8.2s "fix" is not a fix. **The tier +stays.** A fixed timeout is the wrong shape for the underlying problem — the +cases where a long hold is pure cost are exactly those where no further speech +ever arrives — but that is a redesign, and a threshold on the audio score cannot +discriminate: the fragment scores 0.054 and the closer it must not catch scores +0.115. + +So `MaxDeadAir` and a per-cell dead-air gate now exist, measuring speech end → +turn accepted. Current: p50 560–699ms, p95 1.6–2.2s across the gated cells. + +**Dead air immediately found something unrelated.** On +`deepgram-nova/lexical` a spoken account number sits at **7.5s** — reproducible, +and against 0.4–2.1s in all eleven other cells. Root cause: +`_maybe_start_endpointer` arms the VAD endpointing fast path only when the +detector exposes an audio EOU model, so `LexicalTurnDetector` (text-only) never +arms it, nothing ever sends Deepgram a `Finalize`, and the commit waits on Nova's +own endpointing. `local` commits the same audio in 750ms. Flux hides it entirely +by endpointing itself. The fast path's value — telling the STT to stop — is +independent of *how* EOU was decided, so the one configuration that needs it +most is the one architecturally forbidden from having it. + +Getting there killed three hypotheses, each of which looked right: + +- **Namo mis-scoring digit strings.** It scores them 0.987–1.000, complete. +- **The stale-partial watchdog rescuing a stranded turn.** The committed text is + numeral-formatted (`"447291"`) while every partial was word-formatted, so the + commit is Nova's own `smart_format` final, not a synthesized rescue. +- **`_endpoint_text_score` routing past Namo.** Real bug — the chain checks + `effective_text_eou` then `fallback_text_eou`, and `LexicalTurnDetector` names + its predictor `text_eou`, so the endpointer scored partials with the + punctuation baseline. Fixing it changed dead air by 0ms, because that method is + only ever called by an armed endpointer, which under `lexical` never exists. + Dead code for the detector it names. + +None of the three was visible in pass/fail or in `eou→audio`. + **Parallelism turned out to be nearly free, which was not the expectation.** `--jobs` was built assuming concurrent sessions would contend for Silero and Smart Turn inference and inflate `eou→audio`, so the gate refuses to compare runs @@ -380,8 +448,14 @@ STT providers drift under us and yesterday's ceiling is tomorrow's false alarm: |---|---| | a scenario's pass rate drops | speedups | | ghost turns increase | brand-new scenarios (nothing to compare) | -| median latency worsens >15% | latency with fewer than 20 samples | -| | latency measured at a different `--jobs` than the baseline | +| median `eou→audio` worsens >15% | either timing with fewer than 20 samples | +| median dead air worsens >15% | either timing measured at a different `--jobs` | + +Both timings gate through the same `_compare_timing` helper. That is deliberate +rather than tidiness: the latency block used to `return` early on a `--jobs` +mismatch, and a dead-air check bolted on after it would have been skipped +silently on exactly the parallel runs people actually use — the same shape of +blind spot the dead-air metric exists to close. **Latency gates on p50, not p95.** With ~8 latency samples, p95 is the maximum in disguise: one slow turn moved it 394ms → 477ms on an unchanged tree while all five diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index a8f08687..ca04a128 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -3,16 +3,19 @@ "label": "deepgram-flux/lexical", "stt": "deepgram-flux", "detector": "lexical", - "runs": 34, - "passed": 34, + "runs": 33, + "passed": 33, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 227.8, - "latency_p95": 330.2, - "latency_min": 171.4, - "latency_max": 432.0, + "latency_p50": 219.7, + "latency_p95": 321.5, + "latency_min": 166.7, + "latency_max": 362.3, "latency_samples": 50, + "dead_air_p50": 724.6, + "dead_air_p95": 2166.8, + "dead_air_samples": 49, "per_scenario": { "banking_correction": 1.0, "banking_digits": 1.0, @@ -24,7 +27,6 @@ "coding_followup_after_reply": 1.0, "coding_pause": 1.0, "coding_simple": 1.0, - "food_backchannel": 1.0, "food_barge_in": 1.0, "food_list_pause": 1.0, "food_long_pause": 1.0, @@ -53,11 +55,12 @@ "known_failures": [ "banking_confirmation", "coding_double_pause", + "food_backchannel", "medical_hesitant_pause", "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 268.9, + "wall_secs": 270.3, "jobs": 1 }, "deepgram-flux/local": { @@ -69,11 +72,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 226.8, - "latency_p95": 291.8, - "latency_min": 164.7, - "latency_max": 356.3, + "latency_p50": 222.4, + "latency_p95": 273.1, + "latency_min": 168.1, + "latency_max": 316.4, "latency_samples": 52, + "dead_air_p50": 819.4, + "dead_air_p95": 1520.6, + "dead_air_samples": 51, "per_scenario": { "banking_digits": 1.0, "banking_digits_pause": 1.0, @@ -118,7 +124,7 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 262.0, + "wall_secs": 261.7, "jobs": 1 }, "deepgram-flux/provider": { @@ -130,11 +136,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 226.4, - "latency_p95": 320.8, - "latency_min": 171.1, - "latency_max": 396.6, - "latency_samples": 51, + "latency_p50": 219.4, + "latency_p95": 315.8, + "latency_min": 178.2, + "latency_max": 355.8, + "latency_samples": 52, + "dead_air_p50": 550.1, + "dead_air_p95": 1459.8, + "dead_air_samples": 51, "per_scenario": { "banking_digits": 1.0, "banking_short_reject": 1.0, @@ -177,7 +186,7 @@ "support_pause_short" ], "unexpected_passes": [], - "wall_secs": 247.6, + "wall_secs": 246.4, "jobs": 1 } } diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 15e2e542..7aaff3d6 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -21,9 +21,10 @@ import asyncio import time from collections import deque -from collections.abc import AsyncIterator, Callable +from collections.abc import AsyncIterator, Callable, Mapping from contextlib import aclosing from dataclasses import dataclass, field +from typing import Any from scenario import ( AwaitAssistantAudio, @@ -62,6 +63,7 @@ VoiceSession, VoiceSessionEvent, resolve_stt, + resolve_turn_detector, ) from timbal.voice.elevenlabs import ElevenLabsStreamTTS @@ -76,10 +78,21 @@ class HarnessConfig: detector: str = "provider" language: str = "en" dump: bool = False + # Detector attributes to override per run, e.g. + # {"text_complete_hold_timeout_secs": 1.0}. Exists so a parameter sweep can + # ask "what is the right value" instead of editing product constants and + # re-running by hand, which is how the hold tier came to be tested at 0.35 + # and 3.0 and nowhere in between. Applied after construction, so only + # instance attributes — class-level constants must have a matching + # instance attribute to be reachable. + detector_params: Mapping[str, Any] = field(default_factory=dict) @property def label(self) -> str: - return f"{self.stt}/{self.detector}" + if not self.detector_params: + return f"{self.stt}/{self.detector}" + tweaks = ",".join(f"{k}={v}" for k, v in sorted(self.detector_params.items())) + return f"{self.stt}/{self.detector}[{tweaks}]" @dataclass @@ -205,6 +218,26 @@ def stt_config(stt: str, language: str) -> AudioInputConfig: # --------------------------------------------------------------------------- +def _build_detector(config: HarnessConfig) -> Any: + """The detector name, or a configured instance when params are overridden. + + Rejects unknown attribute names rather than silently setting them: a typo in + a sweep would otherwise run the default configuration under a label claiming + it was something else, and every number in the sweep would be wrong in a way + nothing could detect afterwards. + """ + if not config.detector_params: + return config.detector + detector = resolve_turn_detector(config.detector) + for name, value in config.detector_params.items(): + if not hasattr(detector, name): + raise ValueError( + f"{type(detector).__name__} has no attribute {name!r}; cannot override it for {config.label}" + ) + setattr(detector, name, value) + return detector + + async def run_scenario( scenario: Scenario, clips: dict[str, bytes], @@ -231,7 +264,7 @@ async def run_scenario( tts=ElevenLabsStreamTTS(), audio_input=stt_config(config.stt, config.language), audio_output=AudioOutputConfig(model=TTS_MODEL, voice=ASSISTANT_VOICE_ID, sample_rate=SAMPLE_RATE), - turn_detector=config.detector, + turn_detector=_build_detector(config), record_audio=config.dump, ) diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index f247695f..32b35ce6 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -604,8 +604,16 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Say("Actually, cancel that."), *_SETTLE, ], - expect=[UserTurns(2), Interrupted(True), HeardPrefix(max_chars=80), NoGhostTurns(), NoErrors()], + expect=[UserTurns(2), Interrupted(True), HeardPrefix(max_chars=100), NoGhostTurns(), NoErrors()], quick=True, + note=( + "The ceiling was 80 and sat inside the harness's own resolution: playback acks " + "arrive every 250ms, several characters of speech per tick, so runs landed at 82 " + "and 85 with the interrupt working perfectly and a genuine prefix heard. It read " + "as a barge-in regression on a run that had none. 100 leaves room for ack " + "granularity while still separating this from support_barge_in_late (~77+ chars " + "at a 2500ms offset is the contrast being drawn, and that one carries no ceiling)." + ), ), Scenario( id="support_barge_in_late", @@ -820,7 +828,9 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/*": "Nova transcribes the backchannel as 'Mhmm.' and commits it, " "which cuts the assistant off; no detector sees anything to distinguish it from a " "one-word barge-in", - "deepgram-flux/local": "same commit, intermittently — 2/3 at --repeat 3", + "deepgram-flux/*": "same commit, intermittently — Flux usually swallows the sound " + "but lets it through often enough to fail roughly one run in three, under both " + "`local` and `lexical`", }, intermittent=True, note=( @@ -829,7 +839,9 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "acoustically similar and semantically opposite. The split is by STT, not " "detector: Flux and ElevenLabs swallow the sound, Nova transcribes it and all four " "detectors then interrupt on it. Timbal has no notion of a backchannel, so on any " - "STT that transcribes one, an acknowledgement silences the assistant." + "STT that transcribes one, an acknowledgement silences the assistant. Nova fails " + "it every run; Flux leaks it roughly one run in three, which is how it passed " + "three straight repeats under `lexical` before failing a re-baseline." ), ), Scenario( @@ -1029,7 +1041,13 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "carries mid-sentence prosody. `provider` mostly merges it too, but drops to a " "split plus a ghost 'I' about one run in six, visible only under --repeat. That " "ghost was assumed to be about digit strings until medical_filler_midway produced " - "the identical turn on ordinary words." + "the identical turn on ordinary words.\n\n" + "On deepgram-nova/lexical this used to merge and now splits, which is a real " + "change and the right one: the merge was an artifact of Nova taking 7.5s to " + "finalize, long enough to swallow the 1.4s gap whole. Once the endpointer armed " + "for text-only detectors and commits landed at ~1.0s, the pause became visible " + "and that cell splits it — consistent with its 20% pause-merge rate everywhere " + "else. A merge bought with 6.5s of dead air was never worth having." ), ), Scenario( diff --git a/benchmarks/voice/sweep.py b/benchmarks/voice/sweep.py new file mode 100644 index 00000000..33061bcb --- /dev/null +++ b/benchmarks/voice/sweep.py @@ -0,0 +1,164 @@ +"""Parameter sweep: score a detector setting on merges gained against dead air added. + +The hold tier is the worked example. ``TEXT_COMPLETE_HOLD_TIMEOUT_SECS`` ships at +0.35s, and it has been measured at exactly two values: 0.35 (splits four +trailing-modifier scenarios) and 3.0 (fixes 11 scenario-cells and adds 2.6s of +dead air to six barge-in cells). Nobody has tried 0.8, or 1.2. The interesting +question — is there a setting that buys most of the merges for a fraction of the +silence — was unanswerable until dead air became measurable, because a +configuration that merged everything by holding forever looked free. + +Two metrics, deliberately. Optimizing pass rate alone reproduces the mistake this +harness was built to catch:: + + uv run python benchmarks/voice/sweep.py \\ + --param text_complete_hold_timeout_secs --values 0.35,0.8,1.2,2.0,3.0 \\ + --stt deepgram-nova,elevenlabs --detector local --repeat 3 + +Defaults to the pause-merge family (every scenario asserting ``Merged``), since +that is the only family where detectors differ at all — barge-in, plain turns and +silence sit at 100% in all twelve cells and would only add runtime and noise. + +Results are indicative, not conclusive: 38 English scenarios on three backends, +with ten known failures and real intermittency. Treat a winner as a candidate to +confirm against the full grid and the Flux gate, never as a decision. +""" + +from __future__ import annotations + +import argparse +import asyncio +import statistics as st +import sys +import time +from dataclasses import dataclass, field + +from dotenv import load_dotenv +from harness import HarnessConfig, run_scenario +from scenario import SCENARIOS, Merged, Scenario +from synth import synthesize_clips, synthesize_fluent + + +def pause_family() -> list[Scenario]: + """Scenarios that assert a merge — the only discriminating family.""" + return [s for s in SCENARIOS if any(isinstance(e, Merged) for e in s.expect)] + + +@dataclass +class Outcome: + """What one parameter value scored across every cell and repeat.""" + + value: str + passed: int = 0 + total: int = 0 + dead_air: list[float] = field(default_factory=list) + per_scenario: dict[str, list[bool]] = field(default_factory=dict) + wall_secs: float = 0.0 + + @property + def rate(self) -> float: + return self.passed / self.total if self.total else 0.0 + + def summary(self) -> str: + air = f"{st.median(self.dead_air):>6.0f}" if self.dead_air else " -" + p95 = f"{sorted(self.dead_air)[int(0.95 * len(self.dead_air))]:>6.0f}" if self.dead_air else " -" + return f"{self.value:>10} {self.passed:>3}/{self.total:<3} {self.rate:>5.0%} {air}ms {p95}ms" + + +def _coerce(raw: str) -> float | int | bool | str: + for cast in (int, float): + try: + return cast(raw) + except ValueError: + continue + if raw.lower() in ("true", "false"): + return raw.lower() == "true" + return raw + + +async def main() -> int: + parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) + parser.add_argument("--param", required=True, help="detector attribute to vary") + parser.add_argument("--values", required=True, help="comma-separated values to try") + parser.add_argument("--stt", default="deepgram-nova,elevenlabs") + parser.add_argument("--detector", default="local") + parser.add_argument("-s", "--scenario", action="append", help="override the default pause family") + parser.add_argument("--repeat", type=int, default=3, help="runs per scenario per cell (default 3)") + parser.add_argument("--jobs", type=int, default=6) + args = parser.parse_args() + + values = [_coerce(v.strip()) for v in args.values.split(",") if v.strip()] + stts = [v.strip() for v in args.stt.split(",") if v.strip()] + detectors = [v.strip() for v in args.detector.split(",") if v.strip()] + + scenarios = pause_family() + if args.scenario: + wanted = set(args.scenario) + scenarios = [s for s in SCENARIOS if s.id in wanted] + if not scenarios: + print("no scenarios selected") + return 2 + + clips = await synthesize_clips({t for s in scenarios for t in s.standalone_texts()}) + clips.update(await synthesize_fluent([g for s in scenarios for g in s.fluent_groups()])) + + cells = [(stt, det) for stt in stts for det in detectors] + runs = len(values) * len(cells) * len(scenarios) * args.repeat + print(f"\n{runs} runs: {len(values)} values x {len(cells)} cell(s) x {len(scenarios)} scenarios x {args.repeat}") + print(f"varying {args.param} over {values}") + print(f"scenarios: {', '.join(s.id for s in scenarios)}\n") + + semaphore = asyncio.Semaphore(max(1, args.jobs)) + outcomes = {str(v): Outcome(value=str(v)) for v in values} + started = time.monotonic() + + async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: + config = HarnessConfig(stt=stt, detector=det, detector_params={args.param: value}) + async with semaphore: + result = await run_scenario(scenario, clips, config) + out = outcomes[str(value)] + out.total += 1 + out.passed += result.passed + # Only the final commit. Pooling every dead-air sample rewards splitting: + # a merge yields one long wait, a split yields two short ones, so the + # configuration that fragments the utterance scores *better* on silence. + # Final speech end -> final commit is the number a caller actually feels + # and is comparable across both outcomes. + if result.dead_air_ms: + out.dead_air.append(result.dead_air_ms[-1]) + out.wall_secs += result.wall_secs + out.per_scenario.setdefault(scenario.id, []).append(result.passed) + + await asyncio.gather( + *( + one(value, stt, det, scenario) + for value in values + for stt, det in cells + for scenario in scenarios + for _ in range(args.repeat) + ) + ) + + print(f"{args.param:>10} {'merges':<10} {'':>4} {'dead air p50':>10} {'p95':>6}") + for value in values: + print(" " + outcomes[str(value)].summary()) + + print("\nper scenario (pass rate across cells and repeats)\n") + header = "".join(f"{v!s:>9}" for v in values) + print(f" {'scenario':<30}{header}") + for scenario in scenarios: + row = "" + for value in values: + runs_ = outcomes[str(value)].per_scenario.get(scenario.id, []) + row += f"{(sum(runs_) / len(runs_) if runs_ else 0):>8.0%} " + print(f" {scenario.id:<30}{row}") + + print(f"\n elapsed: {time.monotonic() - started:.0f}s") + print("\n A winner here is a candidate, not a decision: confirm it against the full") + print(" 12-cell grid and the Flux gate before believing it.") + return 0 + + +if __name__ == "__main__": + load_dotenv() + sys.exit(asyncio.run(main())) diff --git a/python/timbal/voice/endpointing.py b/python/timbal/voice/endpointing.py index 3f80c78b..7623a38c 100644 --- a/python/timbal/voice/endpointing.py +++ b/python/timbal/voice/endpointing.py @@ -149,9 +149,7 @@ def __init__( min_commit_interval_secs if min_commit_interval_secs is not None else self.MIN_COMMIT_INTERVAL_SECS ) self.text_incomplete_delay_secs = ( - text_incomplete_delay_secs - if text_incomplete_delay_secs is not None - else self.TEXT_INCOMPLETE_DELAY_SECS + text_incomplete_delay_secs if text_incomplete_delay_secs is not None else self.TEXT_INCOMPLETE_DELAY_SECS ) self._score: Callable[[], Awaitable[float | None]] | None = None @@ -302,11 +300,24 @@ async def _run_endpoint(self) -> None: return t0 = time.monotonic() p = await self._score() + p_text: float | None = None + if self._text_score is not None: + try: + p_text = await self._text_score() + except Exception as e: + logger.warning("vad_text_score_failed", error=str(e)) + p_text = None + driver = "audio" if p is None: - # No audio EOU available / not enough buffered signal: never - # force-commit blind — the provider debounce handles it. - logger.debug("vad_endpoint_skipped", reason="no_eou_score") - return + # No audio EOU (text-only detector, or not enough buffered + # signal). Size the delay from the text score instead of + # skipping: the mapping only needs a P(complete), and refusing + # to commit here leaves the turn waiting on the provider's own + # debounce — 7.5s on a spoken account number under Nova. + if p_text is None: + logger.debug("vad_endpoint_skipped", reason="no_eou_score") + return + p, driver = p_text, "text" delay = endpointing_delay( p, min_delay=self.min_delay_secs, @@ -314,22 +325,19 @@ async def _run_endpoint(self) -> None: curve=self.delay_curve, ) text_bumped = False - p_text: float | None = None - if self._text_score is not None: - try: - p_text = await self._text_score() - except Exception as e: - logger.warning("vad_text_score_failed", error=str(e)) - p_text = None - if p_text is not None and p_text < self.TEXT_INCOMPLETE_THRESHOLD: - bumped = max(delay, self.text_incomplete_delay_secs) - text_bumped = bumped > delay - delay = bumped + # Only a bump when text is the *second* opinion. With text driving, + # the incomplete case is already priced into the delay above, and + # applying the floor again would double-count it. + if driver == "audio" and p_text is not None and p_text < self.TEXT_INCOMPLETE_THRESHOLD: + bumped = max(delay, self.text_incomplete_delay_secs) + text_bumped = bumped > delay + delay = bumped # INFO on purpose: fires once per speech-stop and is the whole # observable behaviour of the endpointing fast path. logger.info( "vad_eou_score", p=round(p, 3), + driver=driver, delay_secs=round(delay, 3), score_ms=round((time.monotonic() - t0) * 1000, 1), p_text=round(p_text, 3) if p_text is not None else None, diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index 983801c0..ae0fb923 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -53,6 +53,16 @@ logger = structlog.get_logger("timbal.voice.session") +async def _no_audio_score() -> float | None: + """Audio-EOU scorer for detectors that have none — always abstains. + + Bound instead of the detector's ``score_recent_audio`` so the endpointer + takes its documented "no audio score" path and sizes the delay from the + text EOU, rather than the session having to special-case the binding. + """ + return None + + def _trace_debug_fields() -> dict[str, Any]: """Best-effort tracing ids for debug logs (safe when no RunContext).""" ctx = get_run_context() @@ -411,6 +421,14 @@ def __init__( # unavailable); a VadEndpointer instance = use as-is (custom knobs). self._vad_endpointing = vad_endpointing self._endpointer: VadEndpointer | None = None + # Whether Silero's speech history may be used as *evidence* about the + # user (barge-in vetoes, hold extension), as opposed to merely driving + # the commit fast path. False when the endpointer armed on a text EOU + # alone: those three behaviours were written for detectors that have + # always had an audio model, and switching them on as a side effect of + # a latency fix would change barge-in and hold behaviour under the + # guise of committing sooner. + self._vad_evidence = False # time.monotonic() of the last endpointer-forced stt.commit(); the next # committed transcript within a short window is attributed to it. self._endpoint_commit_sent_at: float | None = None @@ -641,12 +659,7 @@ async def interrupt(self, *, truncate_completed: bool = True) -> None: # SessionInterrupted so the client is not still scheduling backlog PCM # for seconds after a barge-in. dropped_audio = self._drop_queued_audio_output() if was_active else 0 - if ( - was_active - and self._turn_finalized_ok - and truncate_completed - and self._last_interruption_heard_text is None - ): + if was_active and self._turn_finalized_ok and truncate_completed and self._last_interruption_heard_text is None: # The turn completed (AgentTextDone emitted, full reply committed to # transcript/memory) but buffered audio was still playing: rewrite the # committed entry in place to the heard prefix. Checked *after* the @@ -729,10 +742,23 @@ def _start_llm_warmup(self) -> None: async def _maybe_start_endpointer(self) -> None: """Arm the local VAD endpointing loop when the pieces exist. - Requires a turn detector exposing an audio EOU (``score_recent_audio`` - with a non-None ``audio_eou``) and the ``timbal[voice]`` extra for - Silero. Silently stays off otherwise (warning when explicitly - requested). See :mod:`timbal.voice.endpointing`. + Needs the ``timbal[voice]`` extra for Silero, plus *some* EOU signal to + size the delay with: an audio EOU (``score_recent_audio`` with a + non-None ``audio_eou``), or failing that a text EOU. Silently stays off + otherwise (warning when explicitly requested). See + :mod:`timbal.voice.endpointing`. + + Arming without an audio EOU exists because the fast path's job — telling + the STT to finalize — has nothing to do with *how* the turn end was + decided, while the coupling meant the configuration that needs it most + could never have it. A text-only detector on an STT that does not + endpoint aggressively waits on the provider: measured on + deepgram-nova/lexical, a spoken account number sat 7.5s from speech end + to commit, against 750ms for the same audio under ``local``. + + The VAD *evidence* behaviours stay off in that mode — see + :attr:`_vad_evidence`. Silero being loaded is not a reason to start + vetoing barge-ins on a detector that has never done so. """ spec = self._vad_endpointing if spec is False: @@ -740,11 +766,12 @@ async def _maybe_start_endpointer(self) -> None: explicit = spec is not None score_fn = getattr(self.turn_detector, "score_recent_audio", None) audio_eou = getattr(self.turn_detector, "audio_eou", None) - if score_fn is None or audio_eou is None: + has_audio_eou = score_fn is not None and audio_eou is not None + if not has_audio_eou and not self._has_text_eou(): if explicit: logger.warning( "vad_endpointing_unavailable", - reason="turn detector has no audio EOU model", + reason="turn detector exposes neither an audio nor a text EOU", detector=type(self.turn_detector).__name__, ) return @@ -755,7 +782,9 @@ async def _maybe_start_endpointer(self) -> None: else: endpointer = spec endpointer.bind( - score=score_fn, + # No audio EOU: the endpointer falls back to text_score to size the + # delay rather than skipping the commit entirely. + score=score_fn if has_audio_eou else _no_audio_score, commit=self._endpoint_commit, should_commit=self._endpoint_should_commit, text_score=self._endpoint_text_score, @@ -774,10 +803,19 @@ async def _maybe_start_endpointer(self) -> None: logger.warning("vad_endpointer_start_failed", error=str(e)) return self._endpointer = endpointer + self._vad_evidence = has_audio_eou logger.info( "vad_endpointing_active", stop_silence_secs=endpointer.stop_silence_secs, max_delay_secs=endpointer.max_delay_secs, + driver="audio_eou" if has_audio_eou else "text_eou", + ) + + def _has_text_eou(self) -> bool: + """Whether the detector can score a partial's completeness.""" + return any( + getattr(self.turn_detector, name, None) is not None + for name in ("effective_text_eou", "fallback_text_eou", "text_eou") ) def _endpoint_should_commit(self) -> bool: @@ -834,7 +872,7 @@ def _vad_vetoes_barge_in(self, text: str) -> bool: uninterruptible on missing evidence. Speaker echo DOES carry energy, so this gate never vetoes echo; the text-similarity check handles that. """ - if self._endpointer is None: + if self._endpointer is None or not self._vad_evidence: return False speech_secs = self._endpointer.speech_secs_in_window(self.BARGE_IN_VAD_WINDOW_SECS) if speech_secs is None or speech_secs >= self.MIN_BARGE_IN_VAD_SPEECH_SECS: @@ -857,7 +895,7 @@ def _vad_contradicts_recent_partial(self) -> bool: mid-utterance. Conservative on missing evidence (no endpointer / starved VAD → ``False``), mirroring :meth:`_vad_vetoes_barge_in`. """ - if self._endpointer is None: + if self._endpointer is None or not self._vad_evidence: return False speech_secs = self._endpointer.speech_secs_in_window(self.BARGE_IN_VAD_WINDOW_SECS) return speech_secs is not None and speech_secs < self.MIN_BARGE_IN_VAD_SPEECH_SECS @@ -873,7 +911,7 @@ def _vad_confirms_speech_since(self, since_monotonic: float) -> bool: still supersedes via COMMIT). No endpointer → ``True`` so unit tests without Silero keep the partial-extends-hold behavior. """ - if self._endpointer is None: + if self._endpointer is None or not self._vad_evidence: return True window = time.monotonic() - since_monotonic if window <= 0: @@ -944,10 +982,7 @@ async def _sweep_stale_partials(self) -> None: await asyncio.sleep(0.4) if self._closed or not stranded: continue - if ( - self._latest_partial_text == stranded - and self._last_partial_at > self._last_commit_at - ): + if self._latest_partial_text == stranded and self._last_partial_at > self._last_commit_at: logger.info( "stt_stale_partial_synthesized", text_preview=stranded[:80], @@ -1152,8 +1187,7 @@ async def _handle_committed(self, text: str) -> None: if self._endpointer is not None: self._endpointer.notify_committed() vad_endpointed = ( - self._endpoint_commit_sent_at is not None - and time.monotonic() - self._endpoint_commit_sent_at < 2.0 + self._endpoint_commit_sent_at is not None and time.monotonic() - self._endpoint_commit_sent_at < 2.0 ) if vad_endpointed: # INFO: the observable payoff of the fast path — how much sooner @@ -1261,9 +1295,7 @@ async def _handle_committed(self, text: str) -> None: await self.interrupt() self._cancel_turn.clear() # Detector returns the full utterance to hold (refine/merge already applied). - timeout = ( - decision.hold_timeout_secs if decision.hold_timeout_secs is not None else self.hold_timeout_secs - ) + timeout = decision.hold_timeout_secs if decision.hold_timeout_secs is not None else self.hold_timeout_secs await self._arm_hold(final_text, timeout) return @@ -1574,9 +1606,7 @@ async def _run_turn(self, user_text: str) -> None: t.cancel() if self._tts_tasks: try: - await asyncio.shield( - asyncio.gather(*self._tts_tasks, return_exceptions=True) - ) + await asyncio.shield(asyncio.gather(*self._tts_tasks, return_exceptions=True)) except asyncio.CancelledError: pass try: From 107043158716f9a9f5b446f0acb8e98d99982c2b Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 12:41:44 +0200 Subject: [PATCH 07/30] perf(voice): retune the text-complete hold tier from 0.35s to 1.2s MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The tier shortens a HOLD when the audio model says incomplete but the transcript reads finished. 0.35 was chosen on the reasoning that a second tax on top of the endpointer's ~0.5-3s would feel like dead air, and was never revisited, because nothing could price it: eou->audio starts counting at the accepted commit, so hold duration is invisible to it by construction, and pass/fail only ever saw whether a turn merged. Swept once dead air became measurable. Over 0.35/0.8/1.2/2.0/3.0 on the pause-merge family, merges go 58% -> 90% while median dead air stays flat at 793-889ms. That flatness is the finding: the tier fires only when both signals disagree, a minority of turns, so the median cannot move and the cost is entirely in the tail. 0.35 looked free because the median is the wrong statistic for it. Confirmed on the full suite at --repeat 3, 684 runs across all three STT backends under `local`: 84% -> 92% correct, with every scenario this tier exists to protect unchanged at 100% — support_closer, all four barge-ins, banking_short_reject, coding_followup_after_reply. coding_double_pause 33 -> 100%, medical_long_utterance 67 -> 100%, medical_hesitant_pause 0 -> 67%, banking_confirmation 78 -> 100%. One scenario slips, food_trailing_preposition 100 -> 89%, one run in nine. The cost is p95 dead air 1969 -> 2683ms. 3.0 scores higher on merges still (90% vs 81%) and is not worth taking: p95 goes to 3617ms and support_pause_short starts failing, which is a short-pause floor case that should never be affected by a hold at all. Gated Flux cells stay at 100% and their dead-air p50 improved (725->680, 819->615, 550->486ms), so no re-baseline is needed. The sweep also bounds what this knob can do. medical_self_correction tops out at 33% and banking_correction at 22% at every value tried — the two trailing-modifier cases with real consequences, where the agent acts on the retracted half of a self-correction. Their problem is not how long thld runs but that nothing arms one when both signals read finished, so no timeout fixes them. Adds --all to sweep.py: pricing a candidate needs the whole suite, since the cost of holding longer lands on closers and barge-ins that the pause-merge family excludes by construction. --- benchmarks/voice/README.md | 48 ++++++++++++++++++++++----- benchmarks/voice/sweep.py | 8 ++++- python/timbal/voice/turn_detection.py | 23 +++++++++---- 3 files changed, 63 insertions(+), 16 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index a789b88b..26d6b262 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -304,15 +304,45 @@ correct: | `medical_long_utterance` (Nova) | **+8.2s** | counted as a *fix* | Six barge-in cells taking 2.6s longer to answer an ordinary question is not -visible anywhere in pass/fail, and an 8.2s "fix" is not a fix. **The tier -stays.** A fixed timeout is the wrong shape for the underlying problem — the -cases where a long hold is pure cost are exactly those where no further speech -ever arrives — but that is a redesign, and a threshold on the audio score cannot -discriminate: the fragment scores 0.054 and the closer it must not catch scores -0.115. - -So `MaxDeadAir` and a per-cell dead-air gate now exist, measuring speech end → -turn accepted. Current: p50 560–699ms, p95 1.6–2.2s across the gated cells. +visible anywhere in pass/fail, and an 8.2s "fix" is not a fix. So the tier stays +— but **0.35 was the wrong value, and only a sweep could show that**, because +both endpoints look bad from where we were standing. + +`MaxDeadAir` and a per-cell dead-air gate now exist, measuring speech end → turn +accepted, and `sweep.py` can vary a detector parameter without editing product +constants. Sweeping the tier over 0.35 / 0.8 / 1.2 / 2.0 / 3.0 found the shape +nobody had looked for: + +| tier timeout | pause merges | dead air p50 | p95 | +|---|---:|---:|---:| +| 0.35 (was) | 58% | 852ms | 2270ms | +| **1.2** (now) | 81% | 889ms | 1944ms | +| 3.0 | 90% | 844ms | 3617ms | + +**Median dead air is flat across the whole range.** The tier only fires when +audio says incomplete and text says finished — a minority of turns — so the +median cannot move and the cost is entirely a tail effect. That is exactly why +0.35 read as free and went eight months unexamined: the metric that would have +priced it did not exist, and the one that did could not see it. + +Confirmed on the full suite at `--repeat 3`, 684 runs across all three backends +under `local`: correctness **84% → 92%**, with every scenario the tier exists to +protect — `support_closer`, all four barge-ins, `banking_short_reject`, +`coding_followup_after_reply` — unchanged at 100%. `coding_double_pause` goes +33→100%, `medical_long_utterance` 67→100%, `medical_hesitant_pause` 0→67%. The +cost is p95 dead air 1969 → 2683ms. 3.0 scores higher on merges still and is not +worth it: p95 3617ms and `support_pause_short` starts failing. + +The default is now 1.2. The gated Flux cells stayed at 100% and their dead-air +p50 improved (725→680, 819→615, 550→486ms). + +What the sweep also settled is where this knob *stops*. `medical_self_correction` +tops out at 33% and `banking_correction` at 22% — at every value tried. Those are +the two trailing-modifier cases with real consequences, and no hold duration +fixes them, because their problem is not how long the hold runs but that nothing +arms one when both signals read finished. A fixed timeout is the wrong shape for +that, and a threshold on the audio score cannot discriminate either: the fragment +scores 0.054 and the closer it must not catch scores 0.115. **Dead air immediately found something unrelated.** On `deepgram-nova/lexical` a spoken account number sits at **7.5s** — reproducible, diff --git a/benchmarks/voice/sweep.py b/benchmarks/voice/sweep.py index 33061bcb..a5a079d9 100644 --- a/benchmarks/voice/sweep.py +++ b/benchmarks/voice/sweep.py @@ -83,6 +83,12 @@ async def main() -> int: parser.add_argument("--stt", default="deepgram-nova,elevenlabs") parser.add_argument("--detector", default="local") parser.add_argument("-s", "--scenario", action="append", help="override the default pause family") + parser.add_argument( + "--all", + action="store_true", + help="every scenario, not just the pause family — needed to price a winner, since the " + "cost of holding longer lands on closers and barge-ins that the pause family excludes", + ) parser.add_argument("--repeat", type=int, default=3, help="runs per scenario per cell (default 3)") parser.add_argument("--jobs", type=int, default=6) args = parser.parse_args() @@ -91,7 +97,7 @@ async def main() -> int: stts = [v.strip() for v in args.stt.split(",") if v.strip()] detectors = [v.strip() for v in args.detector.split(",") if v.strip()] - scenarios = pause_family() + scenarios = list(SCENARIOS) if args.all else pause_family() if args.scenario: wanted = set(args.scenario) scenarios = [s for s in SCENARIOS if s.id in wanted] diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index e5759d96..0d7e993c 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -669,12 +669,23 @@ class LocalAudioTurnDetector(HeuristicTurnDetector): # with the transcript as the confidence signal): when the audio model says # "incomplete" but the text looks finished (terminal punctuation — Smart # Turn systematically under-scores short closers like "Thank you." / - # "I am David." / "Quite good."), the hold shrinks to this. Keep it short: - # the VAD endpointer has usually already paid ~0.5–3s of silence delay - # before the commit, so a second 1.2s tax felt like dead air on every - # finished utterance Smart Turn under-scored. Both-signals-incomplete - # keeps the full timeout. - TEXT_COMPLETE_HOLD_TIMEOUT_SECS = 0.35 + # "I am David." / "Quite good."), the hold shrinks to this. Both-signals- + # incomplete keeps the full timeout. + # + # Was 0.35 on the reasoning that a second tax on top of the endpointer's + # ~0.5-3s felt like dead air. Swept properly once dead air became + # measurable (benchmarks/voice/sweep.py), across 0.35/0.8/1.2/2.0/3.0 and + # then 0.35 vs 1.2 over 684 runs of the full suite on all three STT + # backends under `local`: correctness 84% -> 92%, with every scenario this + # tier exists to protect — closers, all four barge-ins, short answers — + # unchanged at 100%. The intuition was half right: holding longer does cost + # dead air, but only in the tail (p95 1969 -> 2683ms) because the tier fires + # on a minority of turns. The median does not move (831 -> 842ms), which is + # why 0.35 read as free and was never re-examined. + # + # 3.0 scores higher still on pause merges (90% vs 81%) and is not worth it: + # p95 dead air goes to 3617ms and `support_pause_short` starts failing. + TEXT_COMPLETE_HOLD_TIMEOUT_SECS = 1.2 # The tier needs *confidently* finished text (terminal punctuation scores # P_TERMINAL=0.95), not the predictor's complete-leaning neutral (0.60) — # unpunctuated text must not shorten the hold. From 896514745e18c2daf9e4f5927a3cedf473c9bd87 Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 12:55:40 +0200 Subject: [PATCH 08/30] feat(bench): simulate AEC leak, and find the echo suppressor failing MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit _likely_stt_echo exists so speaker bleed does not make the assistant interrupt itself. Every run of this harness so far — roughly 3,000 of them — fed clean user-only audio, so it had never been exercised once. coding_barge_in_echo proved only that it does not fire on genuine speech, which is the easy half. ScriptFeeder can now mix the assistant's own output back into the mic at a configurable gain (--aec-leak), capped at 1s of buffered audio so TTS running ahead of realtime does not leak the assistant's voice into silence long after it stopped talking. support_echo_silence scripts the case that isolates it: the user says nothing for the entire reply, so anything committed came out of the assistant's own mouth. On deepgram-flux/local it is clean at 0.15, fails 1 in 3 at 0.20, and 4 in 6 at 0.30 — the assistant cutting itself off mid-reply and committing its own words as a user turn. Real barge-in still passes at 0.30, so thisho getting through rather than the suppressor over-firing. The committed ghosts say why: 'Our retailers.', 'Arise retailers.', 'has aroused retailers.' — three manglings of the reply's own tail, '...authorized retailers.' The suppressor is a text-similarity check against what the assistant just said, so echo the STT transcribes badly stops resembling its source and passes the filter built to catch it. Clean echo is suppressed; garbled echo is not, which is the opposite of the intuition that louder bleed is the dangerous case, and it is why the boundary is probabilistic rather than a threshold — it turns on how the STT mis-hears a given phrase, not on gain. No fix here, and text similarity alone cannot carry this. The endpointer's Silero speech history is the obvious corroborating signal and _vad_vetoes_barge_in already uses it, but only when an audio EOU exists. Leak is opt-in and defaults to 0.0. Default suite unchanged: 39 scenarios, three gated Flux cells at 100%.feat(bench): simulate AEC leak, and find the echo suppressor failing _likely_stt_echo exists so speaker bleed does not make the assistant interrupt itself. Every run of this harness so far — roughly 3,000 of them — fed clean user-only audio, so it had never been exercised once. coding_barge_in_echo proved only that it does not fire on genuine speech, which is the easy half. ScriptFeeder can now mix the assistant's own output back into the mic at a configurable gain (--aec-leak), capped at 1s of buffered audio so TTS running ahead of realtime does not leak the assistant's voice into silence long after it stopped talking. support_echo_silence scripts the case that isolates it: the user says nothing for the entire reply, so anything committed came out of the assistant's own mouth. On deepgram-flux/local it is clean at 0.15, fails 1 in 3 at 0.20, and 4 in 6 at 0.30 — the assistant cutting itself off mid-reply and committing its own words as a user turn. Real barge-in still passes at 0.30, so thisho getting through rather than the suppressor over-firing. The committed ghosts say why: 'Our retailers.', 'Arise retailers.', 'has aroused retailers.' — three manglings of the reply's own tail, '...authorized retailers.' The suppressor is a text-similarity check against what the assistant just said, so echo the STT transcribes badly stops resembling its source and passes the filter built to catch it. Clean echo is suppressed; garbled echo is not, which is the opposite of the intuition that louder bleed is the dangerous case, and it is why the boundary is probabilistic rather than a threshold — it turns on how the STT mis-hears a given phrase, not on gain. No fix here, and text similarity alone cannot carry this. The endpointer's Silero speech history is the obvious corroborating signal and _vad_vetoes_barge_in already uses it, but only when an audio EOU exists. Leak is opt-in and defaults to 0.0. Default suite unchanged: 39 scenarios, three gated Flux cells at 100%. --- benchmarks/voice/README.md | 37 ++++++++++++++++++- benchmarks/voice/cli.py | 11 +++++- benchmarks/voice/harness.py | 70 +++++++++++++++++++++++++++++++----- benchmarks/voice/scenario.py | 30 ++++++++++++++++ 4 files changed, 137 insertions(+), 11 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 26d6b262..05e6c4c7 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -28,7 +28,42 @@ production live in that gap. | `score.py` | JSONL records, scorecard aggregation, baseline diffing | | `cli.py` | runner, reporting, regression gate | -Still to come: AEC-leak simulation. +### The echo suppressor fails on echo it cannot read + +`--aec-leak GAIN` mixes the assistant's own output back into the mic, standing in +for an echo canceller that does not fully cancel. Until it existed, all ~3,000 +runs fed clean user-only audio, so `_likely_stt_echo` — the guard that stops the +assistant interrupting itself on speaker bleed — had never once been exercised. +`coding_barge_in_echo` only ever proved it does not fire on genuine speech. + +Measured on `deepgram-flux/local` with `support_echo_silence`, where the user +says nothing at all for the whole reply: + +| leak gain | outcome | +|---|---| +| 0.0 (every prior run) | clean | +| 0.15 | clean | +| 0.20 | 1 failure in 3 | +| 0.30 | **4 failures in 6** | + +Failure means the assistant cut itself off mid-reply and committed its own words +as a user turn. Real barge-in still passes at 0.30, so this is under-suppression, +not over-suppression. + +**The mechanism is the interesting part.** The committed ghosts were `'Our +retailers.'`, `'Arise retailers.'` and `'has aroused retailers.'` — all manglings +of the same phrase from the reply's tail, "...authorized retailers." The +suppressor is a text-similarity check against what the assistant just said, so +echo the STT transcribes *badly enough* stops resembling its source and passes +the filter built to catch it. Clean echo gets suppressed; garbled echo does not, +which inverts the intuition that louder bleed is the dangerous case. + +That also explains why the boundary is probabilistic rather than a threshold: it +depends on how the STT happens to mis-hear a given phrase, not on the gain alone. + +Still to come: a fix for the above — text similarity alone cannot carry this, and +the endpointer's Silero speech history is available as corroborating evidence +(`_vad_vetoes_barge_in` already uses it, but only when an audio EOU exists). ## What it found diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index 75677cde..fb98cb9a 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -126,6 +126,15 @@ async def main() -> int: "--jobs", type=int, default=1, help="concurrent runs; latency is reported but not gated above 1" ) parser.add_argument("--dump", action="store_true", help="write input/output WAVs per run") + parser.add_argument( + "--aec-leak", + type=float, + default=0.0, + metavar="GAIN", + help="mix the assistant's own output back into the mic at this gain (0.1-0.3 is a " + "realistic imperfect echo canceller); exercises the echo suppressor, which clean " + "user-only audio never does", + ) parser.add_argument("--quick", action="store_true", help="representative subset (one per domain)") parser.add_argument("--quiet", action="store_true", help="hide the per-event stream") parser.add_argument("--list", action="store_true", help="list scenarios and exit") @@ -148,7 +157,7 @@ async def main() -> int: jobs = max(1, args.jobs) repeats = max(1, args.repeat) cells = [ - HarnessConfig(stt=stt, detector=detector, language=args.language, dump=args.dump) + HarnessConfig(stt=stt, detector=detector, language=args.language, dump=args.dump, aec_leak=args.aec_leak) for stt in _values(args.stt, "deepgram-flux") for detector in _values(args.detector, "provider") ] diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 7aaff3d6..8b7a1a14 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -18,6 +18,7 @@ from __future__ import annotations +import array import asyncio import time from collections import deque @@ -37,6 +38,7 @@ from synth import ( ASSISTANT_VOICE_ID, BYTES_PER_SECOND, + FRAME_BYTES, FRAME_SECS, HERE, SAMPLE_RATE, @@ -86,13 +88,18 @@ class HarnessConfig: # instance attributes — class-level constants must have a matching # instance attribute to be reachable. detector_params: Mapping[str, Any] = field(default_factory=dict) + # Fraction of the assistant's own output mixed back into the mic, standing + # in for imperfect echo cancellation. 0.0 is every run before this one. + aec_leak: float = 0.0 @property def label(self) -> str: - if not self.detector_params: - return f"{self.stt}/{self.detector}" - tweaks = ",".join(f"{k}={v}" for k, v in sorted(self.detector_params.items())) - return f"{self.stt}/{self.detector}[{tweaks}]" + suffix = "" + if self.aec_leak: + suffix += f"[leak={self.aec_leak}]" + if self.detector_params: + suffix += "[" + ",".join(f"{k}={v}" for k, v in sorted(self.detector_params.items())) + "]" + return f"{self.stt}/{self.detector}{suffix}" @dataclass @@ -165,16 +172,56 @@ def played_ms(self) -> float: return self.played_bytes / self._bps * 1000 +def mix_pcm16(base: bytes, leak: bytes, gain: float) -> bytes: + """Sum two PCM16 frames with ``leak`` attenuated, clipping at int16 bounds.""" + out = array.array("h", base) + other = array.array("h", leak) + for i in range(min(len(out), len(other))): + out[i] = max(-32768, min(32767, int(out[i] + other[i] * gain))) + return out.tobytes() + + class ScriptFeeder: - """Paced PCM source: clip audio when speaking, silence the rest of the time.""" + """Paced PCM source: clip audio when speaking, silence the rest of the time. + + With ``leak_gain`` above zero it also mixes the assistant's own output back + into the mic, standing in for an echo canceller that does not fully cancel. + Every run before this fed clean user-only audio, which means + ``_likely_stt_echo`` — the guard that stops the assistant interrupting + itself on speaker bleed — had never once been exercised. + """ + + # Cap on buffered assistant audio. TTS generates faster than realtime, so an + # uncapped buffer would drift seconds behind and leak the assistant's voice + # into silence long after it stopped speaking — a harsher and less realistic + # test than the thing being simulated. + MAX_LEAK_SECS = 1.0 - def __init__(self) -> None: + def __init__(self, leak_gain: float = 0.0) -> None: self._pending: deque[bytes] = deque() + self._leak = bytearray() + self._leak_gain = leak_gain + self._max_leak_bytes = int(BYTES_PER_SECOND * self.MAX_LEAK_SECS) self._stopped = False def push(self, pcm: bytes) -> None: self._pending.extend(frames(pcm)) + def push_leak(self, pcm: bytes) -> None: + """Queue assistant output to bleed into the mic.""" + if self._leak_gain <= 0: + return + self._leak.extend(pcm) + if len(self._leak) > self._max_leak_bytes: + del self._leak[: len(self._leak) - self._max_leak_bytes] + + def _next_leak(self) -> bytes | None: + if self._leak_gain <= 0 or len(self._leak) < FRAME_BYTES: + return None + frame = bytes(self._leak[:FRAME_BYTES]) + del self._leak[:FRAME_BYTES] + return frame + async def drain(self) -> None: while self._pending: await asyncio.sleep(FRAME_SECS) @@ -192,7 +239,10 @@ async def stream(self) -> AsyncIterator[bytes]: """ next_at = time.monotonic() while not self._stopped: - yield self._pending.popleft() if self._pending else SILENCE_FRAME + frame = self._pending.popleft() if self._pending else SILENCE_FRAME + if (leak := self._next_leak()) is not None: + frame = mix_pcm16(frame, leak, self._leak_gain) + yield frame next_at += FRAME_SECS await asyncio.sleep(max(0.0, next_at - time.monotonic())) @@ -268,7 +318,7 @@ async def run_scenario( record_audio=config.dump, ) - feeder = ScriptFeeder() + feeder = ScriptFeeder(leak_gain=config.aec_leak) playback = PlaybackSim() assistant_speaking = asyncio.Event() # session.close() interrupts any reply still playing. That teardown interrupt @@ -341,7 +391,7 @@ async def drive() -> None: acker: asyncio.Task[None] | None = None try: async for event in stream: - _observe(event, result, playback, assistant_speaking, closing, emit) + _observe(event, result, playback, feeder, assistant_speaking, closing, emit) if isinstance(event, SessionStarted): started = time.monotonic() acker = asyncio.create_task(ack_loop()) @@ -375,6 +425,7 @@ def _observe( event: VoiceSessionEvent, result: RunResult, playback: PlaybackSim, + feeder: ScriptFeeder, assistant_speaking: asyncio.Event, closing: asyncio.Event, emit: Logger, @@ -382,6 +433,7 @@ def _observe( if isinstance(event, AudioOutput): # Individual chunks are far too chatty to log; the playhead is what matters. playback.on_emit(len(event.data)) + feeder.push_leak(event.data) assistant_speaking.set() result.audio_chunks += 1 result.audio_bytes += len(event.data) diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 32b35ce6..7f68e1b1 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -715,6 +715,36 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "only prosody says otherwise." ), ), + Scenario( + id="support_echo_silence", + domain="support", + replies=[_RETURN_POLICY_REPLY], + script=[ + Say("Tell me about your return policy."), + # The user says nothing for the whole reply. Anything committed here + # came out of the assistant's own mouth. + AwaitAssistantDone(), + Silence(4.0), + ], + expect=[UserTurns(1), Interrupted(False), NoGhostTurns(), NoErrors()], + note=( + "Run with --aec-leak to bleed the assistant's output back into the mic. " + "`_likely_stt_echo` exists so speaker bleed does not make the assistant " + "interrupt itself, and until this scenario nothing had ever fed it echo: every " + "run was clean user-only audio. coding_barge_in_echo proves the suppressor does " + "not fire on genuine speech; this is the other half.\n\n" + "Measured on deepgram-flux/local: clean at 0.0 and 0.15, intermittent from 0.20, " + "and 4 failures in 6 at 0.30 — where the assistant cuts itself off mid-reply and " + "commits its own words as a user turn. Real barge-in still works at 0.30, so the " + "suppressor is letting echo through rather than over-suppressing.\n\n" + "The mechanism is visible in what gets committed: 'Our retailers.', 'Arise " + "retailers.', 'has aroused retailers.' — all manglings of the reply's own tail, " + "'...authorized retailers.' The suppressor is a text-similarity check against " + "what the assistant said, so echo that the STT transcribes *badly* stops " + "resembling its source and passes the very filter built to catch it. Louder, " + "cleaner echo would be caught; garbled echo is not." + ), + ), Scenario( id="support_silence_only", domain="support", From d9c11e63beab96e091be5b6f5f98262338c9b82e Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 13:09:11 +0200 Subject: [PATCH 09/30] docs(bench): record the echo-suppressor proof and the fix that failed MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Two findings from the AEC leak work, neither of which changes product code. _likely_stt_echo's fuzzy branch is unreachable for any reply longer than about 100 characters. SequenceMatcher.ratio() is 2M/(len(c)+len(tail)) with M <= len(c), and the tail is sized at max(3*len(c), 100), so the score is capped at 0.50 against a 0.68 gate — a perfect match scores well under the threshold. It can only fire while the assistant's whole reply is still shorter than the window, which is why every observed ghost came from the tail of a long reply and none was an exact substring. A best-window comparison was tried and reverted. It separates the recorded ghosts (0.615-0.963) from clean user phrases (0.340-0.500) cleanly, and takes support_echo_silence at 0.30 leak from 4-in-6 failing to 6/6 passing — while breaking barge-in outright. support_barge_in passes at 0.30 leak today and failed every run with the change, leaving the assistant uninterruptible, which is the worse of the two failures. The threshold was set against the wrong sample. Under leak the STT transcribes a blend of user speech and echo, not one or the other, and the blend lands between the distributions that looked so well separated on clean phrases. There are not two populations here to threshold apart. That leaves the audio reference — correlating the mic against recently played output, the way real AEC does, with both signals already available to the session. Silero is not the alternative despite being to hand: _vad_vetoes_barge_in already notes that speaker echo carries energy, so VAD cannot distinguish it from speech. --- benchmarks/voice/README.md | 39 +++++++++++++++++++++++++++++++++++--- 1 file changed, 36 insertions(+), 3 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 05e6c4c7..18e60a0e 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -61,9 +61,42 @@ which inverts the intuition that louder bleed is the dangerous case. That also explains why the boundary is probabilistic rather than a threshold: it depends on how the STT happens to mis-hear a given phrase, not on the gain alone. -Still to come: a fix for the above — text similarity alone cannot carry this, and -the endpointer's Silero speech history is available as corroborating evidence -(`_vad_vetoes_barge_in` already uses it, but only when an audio EOU exists). +**The fuzzy branch of that check is unreachable, provably.** `_likely_stt_echo` +falls back to `SequenceMatcher(c, tail).ratio() >= 0.68`, where `tail` is +`max(3*len(c), 100)` characters. Since `ratio()` is `2M/(len(c)+len(tail))` with +`M <= len(c)`, sizing the tail at three times the commit caps the score at +exactly **0.50** — a *perfect* match scores well under the threshold: + +| commit chars | tail chars | best possible ratio | +|---:|---:|---:| +| 10 | 100 | 0.182 | +| 33 | 100 | 0.496 | +| 60 | 180 | 0.500 | +| 200 | 400 | 0.667 | + +It can only fire while the assistant's whole reply is still shorter than the +~100-char window. Echo is guarded during the opening of a reply and unguarded for +the rest of it, with nothing but exact-substring matching left — which is why +every ghost came from the tail of a long reply and every one was a near-miss. + +**A window-matching fix was tried and reverted.** Replacing the whole-string +ratio with a best-window comparison separates the recorded ghosts (0.615–0.963) +from clean user phrases (0.340–0.500) with a clear gap, and at a 0.58 threshold +it takes `support_echo_silence` at 0.30 leak from 4-in-6 failing to 6/6 passing. +It also breaks barge-in outright: `support_barge_in`, which passes at 0.30 leak +today, fails every run, and the assistant becomes uninterruptible — the worse +failure of the two. + +The flaw was in how the threshold was set. Scoring *clean* user phrases against +the reply is the wrong sample: under leak the STT transcribes a **blend** of user +speech and echo, and the blend lands between the two distributions rather than +inside the genuine one. No threshold on that comparison separates them, because +the thing being measured is not two populations but a continuum. + +Which leaves the audio reference. Real AEC correlates the mic against recently +played output, and the harness already has both signals. Note that Silero is +*not* the answer despite being available: `_vad_vetoes_barge_in` says plainly +that speaker echo carries energy, so VAD cannot tell it from speech. ## What it found From 9b6da832fccb9626fb74b2ce3c6c0268f6983248 Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 16:52:47 +0200 Subject: [PATCH 10/30] test(bench): gate seven cells instead of three MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Nova and ElevenLabs were measured on every run and gated nothing, so nine of twelve cells could regress silently — including the four where the detector does real work, which is where the tier retune and the endpointer fix both moved behaviour. Censused those nine at --repeat 3 (1,041 runs): 77 failing scenario-cells, but not 77 findings. 29 belong to `heuristic` and 24 to `provider`, and neither can hold a mid-sentence pause off Flux at all — one has no EOU model, the other delegates to an STT that is not endpointing. Marking those 53 would record a single architectural fact 53 times and turn known_failure into wallpaper. So deepgram-nova and elevenlabs x local and lexical are baselined at 100%, taking the gate from 3 cells to 7, at a cost of 24 cell-scoped markers each citing a measured rate. deepgram-flux/heuristic and heuristic/provider on the other two backends stay measured and reported but ungated: their pause failures are a property of picka detector with nothing to hold with. Markers cite three shared reasons rather than 24 bespoke ones — _TEXT_ONLY_PAUSE_SHORTFALL, _AUDIO_PAUSE_SHORTFALL, _EL_OVERMERGE — so a fix to any one shows up as a block of unexpected passes rather than a scatter to chase individually. Known failures are 18 of 39 scenarios now, which is high. It is also concentrated: nova/lexical carries 13 of them and scores 20% on pause merges by measurement, so the ratio reflects a detector limit rather than a suite that has given up. support_trailing_conjunction picked up an elevenlabs/lexical marker after passing 3/3 in the census and failing the confirmation run — 3/4, marked intermittent. All seven cells were baselined serially in this pass, including the three Flux cells, which had been holding pre-retune dead-air numbers (725/819/550ms) the gate only had slack against. They now read 668/656/489ms against the 1.2s tier the code actually ships. --- benchmarks/voice/README.md | 48 ++++- benchmarks/voice/baseline.json | 327 +++++++++++++++++++++++++++++---- benchmarks/voice/scenario.py | 86 ++++++++- 3 files changed, 416 insertions(+), 45 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 18e60a0e..0c49e17f 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -260,12 +260,42 @@ mid-phrase survives a transcript that reads like a finished sentence, and text alone does not. If Timbal is ever pointed at a plain streaming ASR, `local` is the default and `provider` is close to unusable for pauses. -Two caveats. Nova and ElevenLabs are not baselined — several cells have genuine -failures that would need per-cell `known_failure` markers first, so only the Flux -column is gated today. And ElevenLabs drops content on hard inputs independently of -turn-taking (it committed "I'd like to order a large" and silently lost the pizza), -which `ContentPreserved` now catches but which is an STT-quality difference rather -than a turn-taking one. +One caveat: ElevenLabs drops content on hard inputs independently of turn-taking +(it committed "I'd like to order a large" and silently lost the pizza), which +`ContentPreserved` now catches but which is an STT-quality difference rather than +a turn-taking one. + +### Seven cells gate, five do not, and that is deliberate + +A census of the nine ungated cells at `--repeat 3` (1,041 runs) turned up 77 +failing scenario-cells. Marking all 77 would have been the wrong answer, because +they are not 77 findings: + +| detector | unmarked failing cells | +|---|---:| +| `heuristic` | 29 | +| `provider` | 24 | +| `lexical` | 14 | +| `local` | 10 | + +`heuristic` has no EOU model at all and `provider` delegates to the STT, so +neither can hold a mid-sentence pause on a backend that does not endpoint for +them. Their 53 failures are one architectural fact recorded 53 times, and +marking them would turn `known_failure` from a record of defects into wallpaper. + +So the four cells where the detector does real work — `deepgram-nova` and +`elevenlabs` × `local` and `lexical` — are now baselined, taking the gate from 3 +cells to **7**. That cost 24 cell-scoped markers, each citing a measured rate. +The remaining five (`deepgram-flux/heuristic`, and `heuristic`/`provider` on both +other backends) are measured on every run and reported, but not gated: their +pause-family failures are a property of choosing a detector with nothing to hold +with, which is what the detector table above is for. + +The markers cluster into three named reasons rather than 24 bespoke ones — +`_TEXT_ONLY_PAUSE_SHORTFALL` (Namo alone cannot hold the pause off Flux), +`_AUDIO_PAUSE_SHORTFALL` (Smart Turn hears it but the hold does not survive), and +`_EL_OVERMERGE` — so a fix to any one of them shows up as a block of unexpected +passes rather than a scatter. The ranking survived the suite growing to 38 (numbers are not comparable to the table above — the added scenarios are deliberately harder): `local` 92/81/92, @@ -401,8 +431,10 @@ protect — `support_closer`, all four barge-ins, `banking_short_reject`, cost is p95 dead air 1969 → 2683ms. 3.0 scores higher on merges still and is not worth it: p95 3617ms and `support_pause_short` starts failing. -The default is now 1.2. The gated Flux cells stayed at 100% and their dead-air -p50 improved (725→680, 819→615, 550→486ms). +The default is now 1.2. The gated Flux cells stayed at 100% and their dead-air p50 +improved, so they were re-baselined serially against the new default rather than +left holding pre-retune numbers the gate would have had slack against +(725→668, 819→656, 550→489ms). What the sweep also settled is where this knob *stops*. `medical_self_correction` tops out at 33% and `banking_correction` at 22% — at every value tried. Those are diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index ca04a128..20e86a2b 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -3,19 +3,19 @@ "label": "deepgram-flux/lexical", "stt": "deepgram-flux", "detector": "lexical", - "runs": 33, - "passed": 33, + "runs": 34, + "passed": 34, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 219.7, - "latency_p95": 321.5, - "latency_min": 166.7, - "latency_max": 362.3, - "latency_samples": 50, - "dead_air_p50": 724.6, - "dead_air_p95": 2166.8, - "dead_air_samples": 49, + "latency_p50": 234.9, + "latency_p95": 337.2, + "latency_min": 175.9, + "latency_max": 434.9, + "latency_samples": 51, + "dead_air_p50": 667.6, + "dead_air_p95": 2119.1, + "dead_air_samples": 48, "per_scenario": { "banking_correction": 1.0, "banking_digits": 1.0, @@ -45,6 +45,7 @@ "support_barge_in_late": 1.0, "support_barge_in_one_word": 1.0, "support_closer": 1.0, + "support_echo_silence": 1.0, "support_pause": 1.0, "support_pause_short": 1.0, "support_silence_only": 1.0, @@ -60,26 +61,26 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 270.3, + "wall_secs": 276.2, "jobs": 1 }, "deepgram-flux/local": { "label": "deepgram-flux/local", "stt": "deepgram-flux", "detector": "local", - "runs": 32, - "passed": 32, + "runs": 33, + "passed": 33, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 222.4, - "latency_p95": 273.1, - "latency_min": 168.1, - "latency_max": 316.4, - "latency_samples": 52, - "dead_air_p50": 819.4, - "dead_air_p95": 1520.6, - "dead_air_samples": 51, + "latency_p50": 227.9, + "latency_p95": 292.5, + "latency_min": 176.4, + "latency_max": 319.5, + "latency_samples": 50, + "dead_air_p50": 655.5, + "dead_air_p95": 1825.7, + "dead_air_samples": 49, "per_scenario": { "banking_digits": 1.0, "banking_digits_pause": 1.0, @@ -108,6 +109,7 @@ "support_barge_in_late": 1.0, "support_barge_in_one_word": 1.0, "support_closer": 1.0, + "support_echo_silence": 1.0, "support_pause": 1.0, "support_pause_short": 1.0, "support_silence_only": 1.0, @@ -124,7 +126,7 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 261.7, + "wall_secs": 275.5, "jobs": 1 }, "deepgram-flux/provider": { @@ -136,14 +138,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 219.4, - "latency_p95": 315.8, - "latency_min": 178.2, - "latency_max": 355.8, - "latency_samples": 52, - "dead_air_p50": 550.1, - "dead_air_p95": 1459.8, - "dead_air_samples": 51, + "latency_p50": 224.2, + "latency_p95": 333.3, + "latency_min": 171.0, + "latency_max": 478.7, + "latency_samples": 56, + "dead_air_p50": 488.6, + "dead_air_p95": 1447.7, + "dead_air_samples": 53, "per_scenario": { "banking_digits": 1.0, "banking_short_reject": 1.0, @@ -151,7 +153,6 @@ "coding_barge_in_echo": 1.0, "coding_followup_after_reply": 1.0, "coding_simple": 1.0, - "food_backchannel": 1.0, "food_barge_in": 1.0, "food_list_pause": 1.0, "food_long_pause": 1.0, @@ -168,6 +169,7 @@ "support_barge_in_late": 1.0, "support_barge_in_one_word": 1.0, "support_closer": 1.0, + "support_echo_silence": 1.0, "support_pause": 1.0, "support_silence_only": 1.0, "support_simple": 1.0, @@ -180,13 +182,274 @@ "banking_digits_pause", "coding_double_pause", "coding_pause", + "food_backchannel", "medical_filler_midway", "medical_hesitant_pause", "medical_self_correction", "support_pause_short" ], "unexpected_passes": [], - "wall_secs": 246.4, + "wall_secs": 253.1, + "jobs": 1 + }, + "deepgram-nova/lexical": { + "label": "deepgram-nova/lexical", + "stt": "deepgram-nova", + "detector": "lexical", + "runs": 26, + "passed": 26, + "pass_rate": 1.0, + "ghost_turns": 1, + "errors": 0, + "latency_p50": 225.3, + "latency_p95": 302.6, + "latency_min": 167.3, + "latency_max": 338.0, + "latency_samples": 61, + "dead_air_p50": 563.0, + "dead_air_p95": 2179.0, + "dead_air_samples": 58, + "per_scenario": { + "banking_digits": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_double_pause": 1.0, + "coding_followup_after_reply": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_rapid_fire": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_hesitation": 1.0, + "medical_self_correction": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "banking_digits_pause", + "coding_pause", + "food_backchannel", + "food_list_pause", + "food_pause", + "food_trailing_preposition", + "medical_filler_midway", + "medical_hesitant_pause", + "medical_long_utterance", + "support_pause", + "support_trailing_conjunction" + ], + "unexpected_passes": [], + "wall_secs": 270.2, + "jobs": 1 + }, + "deepgram-nova/local": { + "label": "deepgram-nova/local", + "stt": "deepgram-nova", + "detector": "local", + "runs": 32, + "passed": 32, + "pass_rate": 1.0, + "ghost_turns": 1, + "errors": 0, + "latency_p50": 223.2, + "latency_p95": 311.5, + "latency_min": 173.9, + "latency_max": 407.8, + "latency_samples": 52, + "dead_air_p50": 636.6, + "dead_air_p95": 1870.5, + "dead_air_samples": 51, + "per_scenario": { + "banking_digits": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_double_pause": 1.0, + "coding_followup_after_reply": 1.0, + "coding_pause": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_pause": 1.0, + "food_rapid_fire": 1.0, + "food_simple": 1.0, + "food_trailing_preposition": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_filler_midway": 1.0, + "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0, + "support_trailing_conjunction": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "banking_digits_pause", + "food_backchannel", + "food_list_pause", + "medical_hesitant_pause", + "medical_self_correction" + ], + "unexpected_passes": [], + "wall_secs": 271.9, + "jobs": 1 + }, + "elevenlabs/lexical": { + "label": "elevenlabs/lexical", + "stt": "elevenlabs", + "detector": "lexical", + "runs": 32, + "passed": 32, + "pass_rate": 1.0, + "ghost_turns": 1, + "errors": 0, + "latency_p50": 221.0, + "latency_p95": 367.1, + "latency_min": 183.3, + "latency_max": 700.9, + "latency_samples": 47, + "dead_air_p50": 1446.1, + "dead_air_p95": 2911.6, + "dead_air_samples": 47, + "per_scenario": { + "banking_correction": 1.0, + "banking_digits": 1.0, + "banking_digits_pause": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_double_pause": 1.0, + "coding_followup_after_reply": 1.0, + "coding_pause": 1.0, + "coding_simple": 1.0, + "food_backchannel": 1.0, + "food_barge_in": 1.0, + "food_simple": 1.0, + "food_trailing_preposition": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_filler_midway": 1.0, + "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, + "medical_self_correction": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "food_list_pause", + "food_long_pause", + "food_pause", + "food_rapid_fire", + "medical_hesitant_pause", + "support_trailing_conjunction" + ], + "unexpected_passes": [], + "wall_secs": 311.0, + "jobs": 1 + }, + "elevenlabs/local": { + "label": "elevenlabs/local", + "stt": "elevenlabs", + "detector": "local", + "runs": 31, + "passed": 31, + "pass_rate": 1.0, + "ghost_turns": 1, + "errors": 0, + "latency_p50": 237.4, + "latency_p95": 337.5, + "latency_min": 178.3, + "latency_max": 558.0, + "latency_samples": 48, + "dead_air_p50": 1523.1, + "dead_air_p95": 2837.7, + "dead_air_samples": 47, + "per_scenario": { + "banking_digits": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_double_pause": 1.0, + "coding_followup_after_reply": 1.0, + "coding_pause": 1.0, + "coding_simple": 1.0, + "food_backchannel": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_pause": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_filler_midway": 1.0, + "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0, + "support_trailing_conjunction": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "banking_digits_pause", + "food_list_pause", + "food_rapid_fire", + "food_trailing_preposition", + "medical_hesitant_pause", + "medical_self_correction" + ], + "unexpected_passes": [], + "wall_secs": 309.5, "jobs": 1 } } diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 7f68e1b1..c25fdaff 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -513,6 +513,25 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "its hold to 0.35s" ) +# Off Flux, Namo alone is not enough to hold a mid-sentence pause. Nova commits a +# fragment that reads as a finished sentence and `lexical` has no second opinion to +# contradict it — the audio EOU is exactly what `local` adds, and the gap between +# them on this family is 20% vs 60% (Nova) and 70% vs 80% (ElevenLabs). Marked per +# cell rather than per detector because the same detector merges these on Flux, +# where the provider held the fragment before any detector saw it. +_TEXT_ONLY_PAUSE_SHORTFALL = ( + "text EOU alone cannot hold this pause off Flux: the committed fragment reads finished and nothing contradicts it" +) + +# Even with Smart Turn, some pauses are past what either signal resolves. Kept +# separate from the text-only reason so a fix to one is not credited to the other. +_AUDIO_PAUSE_SHORTFALL = "audio EOU hears the continuation but the hold does not survive this gap" + +# ElevenLabs' endpointer waits longer than Flux's, which helps mid-sentence pauses +# and hurts here: two finished sentences 0.9s apart come back as one turn, in all +# four cells, with no detector given a chance to disagree. +_EL_OVERMERGE = "ElevenLabs merges the two sentences into one turn before any detector sees them" + # Under `provider` the session defers to the STT's endpointing entirely, so none of # Timbal's hold logic runs and whatever Flux decides stands. # Under `provider` there is no Timbal hold to override the STT, so any pause Flux @@ -567,6 +586,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], + known_failure={"deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL}, note=( "Used to split under `provider` and `local` and was marked a known failure for " "both. Fluent synthesis fixed it outright: rendered standalone this fragment " @@ -708,6 +728,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(), NoErrors(), ], + known_failure={ + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL + " — merged 3/4", + }, + intermittent=True, note=( "A dangling coordinating conjunction is the strongest continuation cue in text, so " "this is the pause case text EOU should get right without any help from prosody — " @@ -779,6 +804,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], + known_failure={ + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL + " — merged 2/3", + }, + intermittent=True, quick=True, note=( "Under deepgram-flux + provider, Flux holds through the gap and merges inside " @@ -796,6 +826,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[ContentPreserved(), NoGhostTurns(), NoErrors()], + known_failure={ + "elevenlabs/lexical": "ElevenLabs drops part of the utterance across this gap rather " + "than splitting it — content preserved 1/3" + }, + intermittent=True, note=( "The one scenario whose desired outcome is genuinely ambiguous, so it asserts " "content rather than turn count. At a 3.0s gap both answers are defensible — " @@ -823,6 +858,13 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(), NoErrors(), ], + known_failure={ + "deepgram-nova/local": _AUDIO_PAUSE_SHORTFALL, + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", + "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + }, + intermittent=True, note=( "A pause after a comma mid-enumeration: prosody says continue even though the " "gap is long. Failed on every detector until fluent synthesis; now passes on all " @@ -887,7 +929,16 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(), NoErrors(), ], - note="A stranded preposition: syntactically incomplete, so text EOU should hold without prosody.", + known_failure={ + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", + }, + intermittent=True, + note=( + "A stranded preposition: syntactically incomplete, so text EOU should hold without " + "prosody. It does on Flux and under `local` on Nova — the off-Flux `lexical` failure " + "is the one that should be fixable on text alone, and is not." + ), ), Scenario( id="food_rapid_fire", @@ -900,6 +951,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), NoGhostTurns(), NoErrors()], + known_failure={"elevenlabs/*": _EL_OVERMERGE}, note=( "The inverse of every pause scenario: two genuinely finished sentences separated by " "a short gap, which must *not* merge. The suite is full of cases punishing a split " @@ -986,7 +1038,12 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(min_similarity=0.5), NoErrors(), ], - known_failure={"deepgram-flux/*": _TRAILING_MODIFIER_FAILURE}, + known_failure={ + "deepgram-flux/*": _TRAILING_MODIFIER_FAILURE, + "deepgram-nova/local": _TRAILING_MODIFIER_FAILURE, + "elevenlabs/local": _TRAILING_MODIFIER_FAILURE + " — merged 2/3", + }, + intermittent=True, note=( "Self-repair mid-utterance. 'No wait,' is a complete clause boundary that reads " "finished to text EOU while guaranteeing more speech follows — and committing here " @@ -1008,7 +1065,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(min_similarity=0.5), NoErrors(), ], - known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I}, + known_failure={ + "deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I, + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + }, intermittent=True, note=( "A filler immediately before the gap, which is where hedges actually occur in " @@ -1032,6 +1092,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(1), ContentPreserved(min_similarity=0.8), NoGhostTurns(), NoErrors()], + known_failure={ + "deepgram-nova/lexical": "Nova endpoints at the clause boundaries inside this run-on " + "and text EOU scores each piece finished, so it commits three turns" + }, note=( "Twelve seconds of unbroken speech with several clause boundaries an endpointer " "could mistake for an ending. The longest utterance in the suite by a wide margin; " @@ -1063,7 +1127,12 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(min_similarity=0.4), NoErrors(), ], - known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I}, + known_failure={ + "deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I, + "deepgram-nova/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", + }, intermittent=True, note=( "The hardest merge in the suite: a digit string broken across a pause, with no " @@ -1136,7 +1205,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: known_failure={ "deepgram-flux/local": _TRAILING_MODIFIER_FAILURE, "deepgram-flux/provider": _TRAILING_MODIFIER_FAILURE, + "deepgram-nova/local": _TRAILING_MODIFIER_FAILURE, + "deepgram-nova/lexical": _TRAILING_MODIFIER_FAILURE, + "elevenlabs/local": _TRAILING_MODIFIER_FAILURE + " — merged 1/3", }, + intermittent=True, note=( "Self-correction on a digit string: no lexical context, and committing early sends " "the LLM the wrong account number rather than merely a fragment. The one scenario " @@ -1168,7 +1241,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(min_similarity=0.5), NoErrors(), ], - known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_SPLIT}, + known_failure={ + "deepgram-flux/provider": _FLUX_PROVIDER_SPLIT, + "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + }, intermittent=True, note=( "Baselined as a clean pass until --repeat 3 caught `provider` splitting it once in " From 0c1084d198ac64bcd0cf3cc4b7bc8e57d5134ffb Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 23:00:40 +0200 Subject: [PATCH 11/30] fix(voice): hold through pauses the STT has not transcribed yet MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit A HOLD only extended on a new STT partial, which loses a race the provider creates. When it commits on a short silence, the next fragment's audio is already in flight — measured on ElevenLabs at a 0.3s VAD threshold, ~1.3s before any partial existed to extend on — so a 1.2s hold fired mid-sentence and split the utterance. Holds now also extend on Silero hearing speech, capped at 3s per hold because echo surviving an imperfect canceller carries energy and an uncapped mic-driven hold could be held open for as long as the assistant speaks. This is why the ElevenLabs 1.2s vad_silence_threshold_secs looked load-bearing: at 0.3s the pause-merge family scored 47% against 86% at 1.2s, and that 39-point gap was the provider's VAD doing the holding our own merge path was failing at. It is 6 points now, so the threshold is a tunable rather than a crutch — and the last support_pause marker, deepgram-nova/lexical, is dropped: a text-only detecs no prosody to hold on, so it was expiring mid-pause, and it passes 3/3 now. It was never marked intermittent, so it had been failing reliably. Confirming that on the full matrix caught the gate reporting the fix as a defect. count_ghost_turns asked whether a committed turn resembled *one* script entry at >=0.6, so a correct three-fragment merge — about 2.5x longer than any fragment it was compared against — resembled none of them. `ghost turns 1 -> 3` in exactly the four cells where merging improved, three repeats of coding_double_pause, the only scenario of 38 with three fragments and so the only one that could expose it. It mis-scored the inverse too: medical_long_utterance split three ways counted two ghosts, because a piece of a run-on does not resemble the whole. Turns are matched against a window of the whole script now (best_window, already here for HeardPrefix), since turn boundaries are the thing under test and are not expected to line up with script boundaries. Under three words keeps the pntry rule, or a spurious lone "I" — which Flux really does emit — stops being countable. Chasing two apparent flakes then found the harness mis-measuring ElevenLabs across the whole pause family. 69 failures read `fragments never heard`, the worst class here; 68 were ElevenLabs, over 13 scenarios, concentrated in `provider` (31) and `heuristic` (29) — the two detectors with no Timbal-side endpointing, so the two that wait on the provider's own commit. AwaitCommit sampled its watermark when the last Say *started*, and ElevenLabs commits ~1.6s after speech ends, so the *previous* fragment's commit satisfied the wait meant for the fragment under test. What was left was a 0.8s tail plus a 0.5s drain against a commit needing ~1.0s more, and the turn died in teardown. Nova commits in ~600ms, before the next fragment is spoken, so its watermark stayed honest — the bias tracked commit latency and penalised the slower provider twice. Waits are quiescence-based now: satisfied by an event arriving after the 's audio finished feeding, or by the session going quiet for 1.0s with something already in hand. Requiring only the first was tried and is wrong in the other direction — the provider can hold all the audio it needs before the harness finishes handing the clip over, and food_simple commits '...a large coffee and a croissant' without the final '?' for exactly that reason, so nothing ever arrives "after". That cost 4 runs in a 111-run cell, medical_barge_in_twice taking 46s to fail on three turns it had already committed correctly. The comment arguing for the early watermark was right that the case exists and wrong about which utterance it belonged to. food_long_pause's elevenlabs/lexical marker is dropped with it. It blamed the provider for dropping audio across the gap; the provider splits, 4/4, content intact. Its note also claimed ElevenLabs merged here, which is what one observed turn instead of two looks like if you count turns. Baselines may now be taken in parallel. --update-baseline refused --job> 1 on the grounds that contention would bake the machine's load into the latency the gate compares against; measured on deepgram-nova/local, --quick, 3 repeats, it does not — p50 278ms and p95 407ms at --jobs 6 against 280ms and 453ms serial, the only outlier being a 962ms first-run model load in the *serial* run. eou->audio is mostly spent waiting on STT and TTS sockets rather than competing for CPU. The refusal bought nothing a busy machine at --jobs 1 would not also spoil and priced a baseline at six times what it needs to cost. What keeps it sound is unchanged: a baseline records its own concurrency and latency comparison is declined across a mismatch. Re-baselined: 1386 runs, 12 cells, zero session errors, ghost turns 0 in eleven of twelve. Five Deepgram cells at 100% and --jobs 6, including deepgram-flux/provider at 81/81. The ElevenLabs cells are refused and keep stale --jobs 1 entries, because they are dropping barge-in commits outright: medical_barge_in, support_barge_in, support_barge_in_insta and support_barge_in_late under elevenlabs/lexical went 12/12 to 5/12 in four hours. Not this change — forcing the waits back to resolving immediately reproduces it identically at 0/3, the same scenario passes 3/3 on deepgram-nova/lexical, and ElevenLabs passes 4/4 on non-barge-in scenarios. The trace shows the interrupting turn interrupting and then never committing while invented partials ("I don't know.", "Yeah.") arrive on the trailing silence, each one restarting the 1.2s timer that would have committed it. Also fixes four red tests in python/tests/voice/ that predate this: one asserting the pre-retune 0.35s, and three setting session._endpointer without _vad_evidence, so every test covering VAD veto behaviour was exercising the no-evidence path. sweep.py can vary STT params (stt.*) and no longer buries its own result table under DEBUG logs. --- benchmarks/voice/README.md | 234 ++++++++++++++++++++++ benchmarks/voice/baseline.json | 126 ++++++------ benchmarks/voice/cli.py | 60 +++++- benchmarks/voice/harness.py | 115 +++++++++-- benchmarks/voice/scenario.py | 23 ++- benchmarks/voice/score.py | 41 +++- benchmarks/voice/sweep.py | 65 +++--- python/tests/voice/test_session.py | 58 +++++- python/tests/voice/test_turn_detection.py | 13 +- python/timbal/voice/session.py | 63 ++++++ 10 files changed, 660 insertions(+), 138 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 0c49e17f..49197697 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -501,6 +501,230 @@ The same table is a warning about the latency figures generally: a 15% gate on a statistic that drifts 6% between identical runs has less headroom than it looks like, and any cross-detector comparison under ~20ms is noise. +### ElevenLabs was doing the merging, and that hid a defect in ours + +ElevenLabs' dead air sits at p50 ~1.5s against Deepgram's 0.5–0.7s, which read as +a provider property until someone looked: `default_voice_config_from_env` ships +`vad_silence_threshold_secs=1.2` while Nova ships `endpointing=300`. A 4x +asymmetry, in *our* config, with a written justification on neither. The obvious +move was to cut it toward Nova's and collect the second. + +Sweeping it says the opposite, and says it flatly: + +| `vad_silence_threshold_secs` | pause merges | dead air p50 | p95 | +|---|---:|---:|---:| +| 0.3 | 47% | 728ms | 2388ms | +| 0.5 | 44% | 757ms | 2722ms | +| 0.8 | 59% | 1024ms | 3125ms | +| 1.2 (ships) | **86%** | 1409ms | 2721ms | + +Every millisecond of that 1.5s is buying a merge: 39 points of them for 681ms. +And the per-scenario column says who was earning it — `medical_self_correction` +and `banking_correction`, the two cases the hold-tier sweep above could never fix +at any value, score 100% here and 0% at 0.3. **ElevenLabs' VAD was holding them, +not our detector.** Take its 1.2s away and Timbal's own merge path is exposed at +47%, which is also roughly where `deepgram-nova/lexical` has been sitting all +along at `endpointing=300`. Two findings filed separately were one defect, with a +provider's patience masking it on one backend and not the other. + +That also killed a day of planned work before it started. Switching ElevenLabs to +`commit_strategy="manual"` — Timbal owning endpointing end to end, which sounds +strictly better — is the 0.3 column with extra steps, plus `rate_limited` being a +*fatal* STT message type and the endpointer silently dropping any commit it skips +for `session_gate` or `commit_interval`. + +The defect itself is one line of the `coding_double_pause` trace at 0.3: + +``` +17:19:00 commit "The build fails when I-" audio p=0.007 → HOLD 3.0s +17:19:02 commit "I import the module." audio p=0.035 → HOLD 1.2s +17:19:03 [user starts speaking "inside a test."] +17:19:03 stt_hold_expired ← mid-speech +17:19:04 commit "Inside a test." → 2 turns, FAIL +``` + +`_arm_hold` already refuses to fire mid-utterance — but it keys that on a new STT +*partial* since the commit, and lets Silero only corroborate one, never trigger. +When the provider commits on a short silence the next fragment's audio is in +flight for over a second before any partial exists, so the guard has nothing to +hold on and the timer wins. Silero saw that speech the whole time; the log line +`vad_speech_stop utterance_secs=0.96` sits four lines above the expiry. The +fastest signal in the pipeline was subordinated to the slowest. + +Holds now also extend on mic energy alone (`_vad_hears_speech_now`), capped at +3.0s, re-checked every 500ms: + +| at `vad_silence_threshold_secs=0.3` | pause merges | dead air p50 | p95 | +|---|---:|---:|---:| +| before | 47% | 728ms | 2388ms | +| after | **77%** | 742ms | 2230ms | + +Thirty points for fourteen milliseconds — the tell that those merges were never +being bought with time. They were being lost to a timer firing while the user was +still talking, and waiting for the *user* rather than for a *duration* costs +nothing when the user has in fact stopped. At 1.2 the change is inert (86% → 83%, +inside the noise at n=78), exactly as it should be: ElevenLabs isn't splitting +utterances there, so there is nothing to catch. + +The cap is not decoration. Echo surviving an imperfect canceller carries energy — +see the echo-suppressor section — so without it the assistant's own playback could +hold a turn open for as long as it speaks. + +**What this changes is the shape of the config question, not just a number.** The +gap between an aggressive threshold and the shipped one has gone from 39 points to +six: + +| | pause merges | dead air p50 | +|---|---:|---:| +| 0.3 | 77% | 742ms | +| 1.2 | 83% | 1417ms | + +Six points for 675ms on every turn is a trade worth arguing about; 39 points for +the same 675ms was not. Unresolved deliberately: n=78 on one backend, and the +pause family excludes every barge-in by construction, which is precisely where +holding longer would cost. + +**Confirming the fix on the full matrix caught the harness scoring it wrong.** +The gate reported `ghost turns 1 → 3` (or 4) against baseline in four cells — and +those are exactly the four where merging improved. `count_ghost_turns` asked +whether a committed turn resembled *one* script entry at ≥0.6 similarity, so a +correct three-fragment merge, being about 2.5x longer than any fragment it was +compared against, resembled none of them: + +``` +deepgram-nova/local coding_double_pause turns=1 ghosts=1 passed=True failures=[] + committed: ['The build fails when I import the module. Inside a test.'] + script: ['The build fails when I', 'import the module', 'inside a test.'] +``` + +One turn, zero failures, and the metric calls it invented. Three repeats × the one +scenario in the suite with three fragments, plus one pre-existing real ghost, +accounts for every unit of that "regression" — and it gates. It mis-scored the +inverse too: `medical_long_utterance` split into three commits counted two ghosts, +because a piece of a run-on does not resemble the whole. + +Turns are now matched against a *window* of the whole script (`best_window`, which +already existed for `HeardPrefix`) rather than any single entry, since turn +boundaries are the thing under test and are not expected to line up with script +boundaries. Turns under three words keep the per-entry rule: a one-word needle +finds a passable window in almost any script, and a spurious lone `"I"` turn — +which Flux really does emit — has to stay countable. Across all 38 speaking +scenarios, replayed both as one perfect merge and as perfect per-entry turns, +neither shape now registers a ghost. + +**Chasing two apparent flakes found the harness had been mis-measuring +ElevenLabs on the whole pause family.** 69 failures in the matrix read +`fragments never heard` — the second half of an utterance absent entirely, the +worst failure class here. 68 were ElevenLabs, across 13 scenarios, concentrated +in `provider` (31) and `heuristic` (29): exactly the two detectors with no +Timbal-side endpointing, so exactly the two that wait on the provider's own +commit. + +`AwaitCommit` waited for `len(committed) > base`, with `base` sampled when the +last `Say` *started*. ElevenLabs commits ~1.6s after speech ends, so the +*previous* fragment's commit landed after that sample and satisfied the wait +meant for the fragment under test. What remained was the 0.8s tail plus a 0.5s +drain, against a commit needing ~1.0s. The turn was lost to teardown: + +``` +[+ 3.19s] committed "The pain is, um..." <- fragment 1, 1.7s after it was spoken +[+ 4.05s] await_commit <- satisfied instantly by the line above +[+ 4.67s] partial "Mostly at night." <- fragment 2 arrives + <- teardown ~4.85s. Never committed. +``` + +Nova commits in ~600ms, before the next fragment is even spoken, so its +watermark stays honest — which is why Nova showed real splits while ElevenLabs +showed phantom content loss. The bias tracked provider commit latency, so the +slower provider was penalised for being slow *twice*. + +A count cannot distinguish a commit for the speech just fed from a late one for +earlier speech, so waits are now timed. Anything arriving after the last `Say`'s +audio finished feeding is the answer, because mic audio is paced at realtime and +the provider cannot have been sent a clip it has not received yet. + +That alone is not enough, and the comment it replaced said why: "a fast commit +can land while the clip is still draining". Two different events look like that. +One is this bug — an earlier utterance's commit, arriving late — but the other is +real: the provider can have all the audio it needs before the harness finishes +handing the clip over, and `food_simple` commits `'…a large coffee and a +croissant'` without the final `?` for exactly that reason. Then nothing ever +arrives "after", and a strict timed wait hangs for its full timeout. Requiring it +cost 4 runs in a 111-run cell, `medical_barge_in_twice` taking 46s to fail on +three turns it had already committed correctly. + +So a wait resolves on either: something arriving after the speech, or the session +going quiet for 1.0s with something already in hand. The fallback covers the +early commit, and also covers a final `Say` that correctly produces nothing — +which previously only avoided a timeout by accident, because a stale event +satisfied it. `food_backchannel`'s workaround of dropping the step entirely is no +longer load-bearing, though it is left in place. + +Under the fix `medical_filler_midway` on `elevenlabs/provider` reports the same +thing 3/3: a split, no errors, nothing lost. `food_long_pause` on +`elevenlabs/lexical` goes 1/3 to 4/4 with content intact, and its known failure — +which blamed the provider for dropping audio — is gone. Two things worth +knowing: latency percentiles for affected cells were computed on a biased subset, +since a turn that never commits also never reports `eou→audio` (the repro went +from 3 samples to 6), so the ElevenLabs latency figures recorded before this are +drawn from a biased subset of turns. + +**The re-baseline then caught ElevenLabs dropping barge-in commits outright.** +`medical_barge_in`, `support_barge_in`, `support_barge_in_instant` and +`support_barge_in_late` under `elevenlabs/lexical` went from 12/12 passing to +5/12 in the space of four hours, on cells whose only code change in between was +the harness. The interrupting turn interrupts — `interrupted=True`, heard text +present — and then never commits: + +``` +[+ 4.84s] say "Sorry, one more thing." +[+ 5.02s] partial "I don't know." <- invented; this is what barges in +[+ 7.02s] partial "Sorry, one more thing." <- the real text, as a partial +[+ 8.23s] partial "Yeah." <- invented +[+ 9.24s] partial "Yeah." <- no commit, ever +``` + +Not the harness, and not the hold change: forcing the waits back to resolving +immediately reproduces it identically, 0/3, and the same scenario passes 3/3 on +`deepgram-nova/lexical` while ElevenLabs passes 4/4 on non-barge-in scenarios. The +plausible mechanism is visible in the trace — ElevenLabs hallucinates on the +trailing silence, and with `commit_strategy="vad"` each invented partial restarts +the 1.2s silence timer that would otherwise commit, so the real utterance is held +open indefinitely. That is the same threshold the merge rates depend on, which +makes it a poor thing to be load-bearing twice. + +Consequence for the baseline: 5 of 12 cells carry a current one, all Deepgram, all +at `--jobs 6`. The two ElevenLabs entries are stale — `--jobs 1`, ~31 runs from a +`--quick` subset — and cannot be refreshed while the provider is dropping turns, +since a cell with unmarked failures is refused. Latency there is consequently +ungated on a concurrency mismatch as well. + +Two incidental findings from the same session. `sweep.py` never configured +structlog, so every sweep — including the tier retune above — buried its own +result table under a few hundred thousand DEBUG lines, far enough to be dropped +outright by anything that caps captured output. And `python/tests/voice/` had four +red tests: one asserting the pre-retune `0.35`, and three that set +`session._endpointer` without `_vad_evidence`, which the endpointer-arming fix +split into separate flags — so the tests covering VAD veto behaviour were all +silently exercising the no-evidence path. Both are fixed. The tier assertion also +turned out to be unsatisfiable rather than merely stale: the retune moved the +complete tier to 1.2, which is what `TEXT_INCOMPLETE_HOLD_TIMEOUT_SECS` already +was, so the two confidence tiers now differ only in the logged reason and the +inverse tier has never been re-swept against its new counterpart. + +Baselines may also now be taken in parallel. `--update-baseline` used to refuse +`--jobs > 1`, on the grounds that contention would bake the machine's load into +the latency the gate compares against. Measured on `deepgram-nova/local`, +`--quick`, 3 repeats, it does not: p50 278ms and p95 407ms at `--jobs 6` against +280ms and 453ms serial. `eou→audio` is mostly spent waiting on STT and TTS +sockets rather than competing for CPU, so the sessions overlap their waiting; the +only outlier in either run is a 962ms first-run model load, in the *serial* one. +The refusal bought nothing a busy machine at `--jobs 1` would not also spoil, and +it priced a full baseline at roughly six times what it needs to cost, which is +the kind of price that stops anyone taking one. What makes it sound is unchanged +and unrelated: a baseline records its own concurrency, and latency comparison is +declined across a mismatch. + ## Running ```bash @@ -520,8 +744,18 @@ uv run python benchmarks/voice/cli.py --update-baseline # accept current b # the matrix: --stt and --detector are crossed, one scorecard per cell uv run python benchmarks/voice/cli.py --detector local,lexical,provider --jobs 4 + +# reproduce one cell of a sweep with the event stream visible — the step between +# "this value scores worse" and knowing why +uv run python benchmarks/voice/cli.py -s coding_double_pause --stt elevenlabs \ + --detector local --stt-param vad_silence_threshold_secs=0.3 --verbose ``` +`--stt-param` and `--detector-param` take `KEY=VALUE`. STT keys are checked against +a per-backend allowlist (`harness.SWEEPABLE_STT_KEYS`) because providers ignore +unknown query params in silence: a typo would otherwise sweep one value under four +labels and every number in the table would agree with every other. + Exit code is non-zero when any expectation fails or a regression is gated. ## The matrix diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index 20e86a2b..81614289 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -3,19 +3,19 @@ "label": "deepgram-flux/lexical", "stt": "deepgram-flux", "detector": "lexical", - "runs": 34, - "passed": 34, + "runs": 102, + "passed": 102, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 234.9, - "latency_p95": 337.2, - "latency_min": 175.9, - "latency_max": 434.9, - "latency_samples": 51, - "dead_air_p50": 667.6, - "dead_air_p95": 2119.1, - "dead_air_samples": 48, + "latency_p50": 273.2, + "latency_p95": 363.9, + "latency_min": 196.0, + "latency_max": 508.2, + "latency_samples": 153, + "dead_air_p50": 717.5, + "dead_air_p95": 2170.2, + "dead_air_samples": 150, "per_scenario": { "banking_correction": 1.0, "banking_digits": 1.0, @@ -61,26 +61,26 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 276.2, - "jobs": 1 + "wall_secs": 828.4, + "jobs": 6 }, "deepgram-flux/local": { "label": "deepgram-flux/local", "stt": "deepgram-flux", "detector": "local", - "runs": 33, - "passed": 33, + "runs": 99, + "passed": 99, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 227.9, - "latency_p95": 292.5, - "latency_min": 176.4, - "latency_max": 319.5, - "latency_samples": 50, - "dead_air_p50": 655.5, - "dead_air_p95": 1825.7, - "dead_air_samples": 49, + "latency_p50": 280.4, + "latency_p95": 364.0, + "latency_min": 198.6, + "latency_max": 442.2, + "latency_samples": 151, + "dead_air_p50": 750.0, + "dead_air_p95": 1945.9, + "dead_air_samples": 147, "per_scenario": { "banking_digits": 1.0, "banking_digits_pause": 1.0, @@ -126,26 +126,26 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 275.5, - "jobs": 1 + "wall_secs": 838.0, + "jobs": 6 }, "deepgram-flux/provider": { "label": "deepgram-flux/provider", "stt": "deepgram-flux", "detector": "provider", - "runs": 27, - "passed": 27, + "runs": 81, + "passed": 81, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 224.2, - "latency_p95": 333.3, - "latency_min": 171.0, - "latency_max": 478.7, - "latency_samples": 56, - "dead_air_p50": 488.6, - "dead_air_p95": 1447.7, - "dead_air_samples": 53, + "latency_p50": 275.1, + "latency_p95": 386.9, + "latency_min": 191.8, + "latency_max": 477.2, + "latency_samples": 162, + "dead_air_p50": 554.2, + "dead_air_p95": 1262.7, + "dead_air_samples": 157, "per_scenario": { "banking_digits": 1.0, "banking_short_reject": 1.0, @@ -189,26 +189,26 @@ "support_pause_short" ], "unexpected_passes": [], - "wall_secs": 253.1, - "jobs": 1 + "wall_secs": 783.1, + "jobs": 6 }, "deepgram-nova/lexical": { "label": "deepgram-nova/lexical", "stt": "deepgram-nova", "detector": "lexical", - "runs": 26, - "passed": 26, + "runs": 81, + "passed": 81, "pass_rate": 1.0, - "ghost_turns": 1, + "ghost_turns": 0, "errors": 0, - "latency_p50": 225.3, - "latency_p95": 302.6, - "latency_min": 167.3, - "latency_max": 338.0, - "latency_samples": 61, - "dead_air_p50": 563.0, - "dead_air_p95": 2179.0, - "dead_air_samples": 58, + "latency_p50": 278.8, + "latency_p95": 370.2, + "latency_min": 193.7, + "latency_max": 388.7, + "latency_samples": 159, + "dead_air_p50": 573.2, + "dead_air_p95": 2086.2, + "dead_air_samples": 155, "per_scenario": { "banking_digits": 1.0, "banking_hesitation": 1.0, @@ -233,6 +233,7 @@ "support_barge_in_one_word": 1.0, "support_closer": 1.0, "support_echo_silence": 1.0, + "support_pause": 1.0, "support_pause_short": 1.0, "support_silence_only": 1.0, "support_simple": 1.0 @@ -250,30 +251,29 @@ "medical_filler_midway", "medical_hesitant_pause", "medical_long_utterance", - "support_pause", "support_trailing_conjunction" ], "unexpected_passes": [], - "wall_secs": 270.2, - "jobs": 1 + "wall_secs": 815.3, + "jobs": 6 }, "deepgram-nova/local": { "label": "deepgram-nova/local", "stt": "deepgram-nova", "detector": "local", - "runs": 32, - "passed": 32, + "runs": 96, + "passed": 96, "pass_rate": 1.0, - "ghost_turns": 1, + "ghost_turns": 0, "errors": 0, - "latency_p50": 223.2, - "latency_p95": 311.5, - "latency_min": 173.9, - "latency_max": 407.8, - "latency_samples": 52, - "dead_air_p50": 636.6, - "dead_air_p95": 1870.5, - "dead_air_samples": 51, + "latency_p50": 274.1, + "latency_p95": 355.9, + "latency_min": 195.4, + "latency_max": 446.6, + "latency_samples": 153, + "dead_air_p50": 661.7, + "dead_air_p95": 1880.4, + "dead_air_samples": 150, "per_scenario": { "banking_digits": 1.0, "banking_hesitation": 1.0, @@ -319,8 +319,8 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 271.9, - "jobs": 1 + "wall_secs": 828.1, + "jobs": 6 }, "elevenlabs/lexical": { "label": "elevenlabs/lexical", diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index fb98cb9a..1b316c44 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -39,7 +39,7 @@ import structlog from dotenv import load_dotenv -from harness import HarnessConfig, RunResult, run_scenario +from harness import HarnessConfig, RunResult, coerce_param, run_scenario from scenario import SCENARIOS, Scenario, select from score import ( RunRecord, @@ -84,6 +84,17 @@ def _values(flags: list[str] | None, default: str) -> list[str]: return list(dict.fromkeys(out)) +def _parse_params(flags: list[str] | None) -> dict[str, object]: + """``KEY=VALUE`` flags to a coerced mapping.""" + params: dict[str, object] = {} + for flag in flags or []: + key, _, raw = flag.partition("=") + if not _ or not key.strip(): + raise ValueError(f"expected KEY=VALUE, got {flag!r}") + params[key.strip()] = coerce_param(raw.strip()) + return params + + @dataclass class _Job: config: HarnessConfig @@ -123,7 +134,7 @@ async def main() -> int: parser.add_argument("--language", default="en") parser.add_argument("--repeat", type=int, default=1, help="runs per scenario (variance / flaky detection)") parser.add_argument( - "--jobs", type=int, default=1, help="concurrent runs; latency is reported but not gated above 1" + "--jobs", type=int, default=1, help="concurrent runs; latency gates whenever this matches the baseline's" ) parser.add_argument("--dump", action="store_true", help="write input/output WAVs per run") parser.add_argument( @@ -135,6 +146,20 @@ async def main() -> int: "realistic imperfect echo canceller); exercises the echo suppressor, which clean " "user-only audio never does", ) + # Reproducing one cell of a sweep with the event stream visible was the missing + # step between "this value scores worse" and knowing why. + parser.add_argument( + "--stt-param", + action="append", + metavar="KEY=VALUE", + help="provider STT knob, e.g. vad_silence_threshold_secs=0.3 (see harness.SWEEPABLE_STT_KEYS)", + ) + parser.add_argument( + "--detector-param", + action="append", + metavar="KEY=VALUE", + help="detector attribute, e.g. text_complete_hold_timeout_secs=1.2", + ) parser.add_argument("--quick", action="store_true", help="representative subset (one per domain)") parser.add_argument("--quiet", action="store_true", help="hide the per-event stream") parser.add_argument("--list", action="store_true", help="list scenarios and exit") @@ -156,8 +181,22 @@ async def main() -> int: jobs = max(1, args.jobs) repeats = max(1, args.repeat) + try: + stt_extra = _parse_params(args.stt_param) + detector_params = _parse_params(args.detector_param) + except ValueError as e: + print(e) + return 2 cells = [ - HarnessConfig(stt=stt, detector=detector, language=args.language, dump=args.dump, aec_leak=args.aec_leak) + HarnessConfig( + stt=stt, + detector=detector, + language=args.language, + dump=args.dump, + aec_leak=args.aec_leak, + stt_extra=stt_extra, + detector_params=detector_params, + ) for stt in _values(args.stt, "deepgram-flux") for detector in _values(args.detector, "provider") ] @@ -167,11 +206,16 @@ async def main() -> int: # silently drop every scenario it didn't cover and disarm their gates. print("refusing to update the baseline from a filtered run: it would drop the other scenarios") return 2 - if args.update_baseline and jobs > 1: - # The baseline carries the latency the gate compares against. Recording it - # under contention would bake in whatever else the machine was doing. - print("refusing to update the baseline from a parallel run: measure latency at --jobs 1") - return 2 + # A parallel baseline used to be refused here, on the grounds that contention + # would bake the machine's load into the latency the gate compares against. + # Measured, that does not happen: deepgram-nova/local, --quick, 3 repeats, is + # p50 278ms / p95 407ms at --jobs 6 against 280ms / 453ms serial — no worse, + # because eou→audio is mostly waiting on STT and TTS sockets rather than + # competing for CPU. What keeps this sound is that the baseline records its own + # concurrency and `_compare_latency` declines to compare across a mismatch, so + # a parallel baseline is only ever read by equally parallel runs. The refusal + # bought no protection against a busy machine at --jobs 1 either, and cost a + # ~6x slower baseline, which is the kind of price that stops people taking one. queue: list[_Job] = [] skipped: list[tuple[HarnessConfig, Scenario]] = [] diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 8b7a1a14..b6b1004b 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -88,6 +88,12 @@ class HarnessConfig: # instance attributes — class-level constants must have a matching # instance attribute to be reachable. detector_params: Mapping[str, Any] = field(default_factory=dict) + # Provider STT knobs to override per run, merged over the defaults in + # `stt_config`. The detector is not the only endpointer in the pipeline: + # ElevenLabs ships `vad_silence_threshold_secs=1.2` and Nova ships + # `endpointing=300`, and until these were sweepable the 4x asymmetry + # between them read as a provider property rather than a setting. + stt_extra: Mapping[str, Any] = field(default_factory=dict) # Fraction of the assistant's own output mixed back into the mic, standing # in for imperfect echo cancellation. 0.0 is every run before this one. aec_leak: float = 0.0 @@ -97,8 +103,9 @@ def label(self) -> str: suffix = "" if self.aec_leak: suffix += f"[leak={self.aec_leak}]" - if self.detector_params: - suffix += "[" + ",".join(f"{k}={v}" for k, v in sorted(self.detector_params.items())) + "]" + for params in (self.detector_params, self.stt_extra): + if params: + suffix += "[" + ",".join(f"{k}={v}" for k, v in sorted(params.items())) + "]" return f"{self.stt}/{self.detector}{suffix}" @@ -108,7 +115,18 @@ class RunResult: stt: str detector: str committed: list[str] = field(default_factory=list) + # Arrival times, parallel to `committed` / `replies_spoken`. A wait for "one + # more commit" cannot tell a commit for the speech just fed from one for + # earlier speech that arrived late, and where a provider's commit lags the + # audio by more than the gap between fragments, that is every pause + # scenario it has. See `AwaitCommit` in `drive`. + committed_at: list[float] = field(default_factory=list) replies_spoken: list[str] = field(default_factory=list) + replied_at: list[float] = field(default_factory=list) + # Last time the session said anything at all — partial, commit or reply. What + # "the session has finished with the audio I fed it" is actually made of, + # since neither a count nor a single timestamp can express it. + last_event_at: float = 0.0 interrupted: bool = False heard_text: str | None = None latencies_ms: list[float] = field(default_factory=list) @@ -247,9 +265,42 @@ async def stream(self) -> AsyncIterator[bytes]: await asyncio.sleep(max(0.0, next_at - time.monotonic())) -def stt_config(stt: str, language: str) -> AudioInputConfig: +# STT knobs `--stt-param` may vary, per backend. An allowlist because providers +# ignore unknown query params silently: a typo would sweep one value under +# several labels and every number in the table would agree, convincingly. +SWEEPABLE_STT_KEYS: dict[str, frozenset[str]] = { + "elevenlabs": frozenset( + {"commit_strategy", "min_speech_duration_ms", "vad_silence_threshold_secs", "vad_threshold"} + ), + "deepgram-nova": frozenset({"endpointing", "utterance_end_ms", "smart_format", "punctuate", "interim_results"}), + "deepgram-flux": frozenset({"eot_timeout_ms", "eot_threshold", "eager_eot_threshold"}), +} + + +def coerce_param(raw: str) -> float | int | bool | str: + """Best-effort literal from a command-line value (`0.3` -> float, `true` -> bool).""" + for cast in (int, float): + try: + return cast(raw) + except ValueError: + continue + if raw.lower() in ("true", "false"): + return raw.lower() == "true" + return raw + + +def stt_config(stt: str, language: str, extra: Mapping[str, Any] | None = None) -> AudioInputConfig: + """Provider defaults for a cell, with `extra` merged over them. + + The ElevenLabs values mirror ``timbal.voice.server.default_voice_config_from_env`` + rather than inventing benchmark-only ones — measuring a configuration the + product does not ship would report dead air nobody experiences. + """ + overrides = dict(extra or {}) + if unknown := set(overrides) - SWEEPABLE_STT_KEYS.get(stt, frozenset()): + raise ValueError(f"{stt} has no sweepable STT param(s) {sorted(unknown)}") if stt.startswith("deepgram"): - return AudioInputConfig(language=language, sample_rate=SAMPLE_RATE) + return AudioInputConfig(language=language, sample_rate=SAMPLE_RATE, extra=overrides) return AudioInputConfig( model="scribe_v2_realtime", language=language, @@ -259,6 +310,7 @@ def stt_config(stt: str, language: str) -> AudioInputConfig: "min_speech_duration_ms": 100, "vad_silence_threshold_secs": 1.2, "vad_threshold": 0.4, + **overrides, }, ) @@ -312,7 +364,7 @@ async def run_scenario( agent=agent, stt=resolve_stt(config.stt), tts=ElevenLabsStreamTTS(), - audio_input=stt_config(config.stt, config.language), + audio_input=stt_config(config.stt, config.language, config.stt_extra), audio_output=AudioOutputConfig(model=TTS_MODEL, voice=ASSISTANT_VOICE_ID, sample_rate=SAMPLE_RATE), turn_detector=_build_detector(config), record_audio=config.dump, @@ -345,24 +397,45 @@ async def wait_for(predicate, timeout: float, what: str) -> None: return await asyncio.sleep(FRAME_SECS) + # How long the session must say nothing before a wait accepts what it already + # has. Wide enough to cover the gap between speech ending and the first + # partial for it (~0.4s on ElevenLabs, the slowest measured here). + settle_secs = 1.0 + + def _settled(events: list[float], after: float) -> bool: + """Whether the session is done with the speech fed up to ``after``. + + Anything arriving after that instant is the answer, since mic audio is + paced at realtime and the provider cannot have been sent a clip it has + not received yet. + + Otherwise the provider may simply have answered early — it can have all + the audio it needs before the harness finishes handing the clip over, and + `food_simple` commits without the final "?" for exactly that reason. Then + nothing will ever arrive "after", so a wait for one hangs for its whole + timeout. Falling back to a quiet session with something already in hand + covers that, and covers a last `Say` that correctly produces nothing at + all, which used to depend on a stale event to avoid timing out. + """ + if any(t > after for t in events): + return True + if not events: + return False + return time.monotonic() - max(after, result.last_event_at) >= settle_secs + async def drive() -> None: - # Baselines are taken when speech *starts*, not when the wait step is - # reached: a fast commit can land while the clip is still draining, and a - # wait armed after the fact would sit there until it timed out. - commits_at_say = 0 - replies_at_say = 0 + last_say_ended = 0.0 for step in scenario.script: if isinstance(step, Say): emit("say", f'"{step.text}"') - commits_at_say = len(result.committed) - replies_at_say = len(result.replies_spoken) feeder.push(clips[step.clip_key]) await feeder.drain() # drain() returns once the last frame is pushed, so this is the # instant the speaker fell silent. A later part of the same # fluent utterance overwrites it, leaving the final speech end. result.speech_ended_at = time.monotonic() + last_say_ended = result.speech_ended_at elif isinstance(step, Silence): emit("silence", f"{step.secs:.1f}s") await asyncio.sleep(step.secs) @@ -377,10 +450,18 @@ async def drive() -> None: ) elif isinstance(step, AwaitCommit): emit("await_commit") - await wait_for(lambda base=commits_at_say: len(result.committed) > base, step.timeout, "commit") + await wait_for( + lambda after=last_say_ended: _settled(result.committed_at, after), + step.timeout, + "commit", + ) elif isinstance(step, AwaitAssistantDone): emit("await_reply") - await wait_for(lambda base=replies_at_say: len(result.replies_spoken) > base, step.timeout, "reply") + await wait_for( + lambda after=last_say_ended: _settled(result.replied_at, after), + step.timeout, + "reply", + ) await asyncio.sleep(0.5) # let trailing events land before teardown closing.set() feeder.stop() @@ -440,8 +521,10 @@ def _observe( elif isinstance(event, SessionStarted): emit("session_started") elif isinstance(event, TranscriptPartial): + result.last_event_at = time.monotonic() emit("partial", f'"{event.text}"') elif isinstance(event, TranscriptCommitted): + result.last_event_at = time.monotonic() detail = f'"{event.text}"{" (replace)" if event.replace else ""}' if result.speech_ended_at is not None: dead_air = (time.monotonic() - result.speech_ended_at) * 1000 @@ -451,11 +534,15 @@ def _observe( emit("committed", detail) if event.replace and result.committed: result.committed[-1] = event.text + result.committed_at[-1] = time.monotonic() else: result.committed.append(event.text) + result.committed_at.append(time.monotonic()) elif isinstance(event, AgentTextDone): + result.last_event_at = time.monotonic() emit("agent_done", f'"{event.text}"') result.replies_spoken.append(event.text) + result.replied_at.append(time.monotonic()) assistant_speaking.clear() elif isinstance(event, SessionInterrupted): playback.on_interrupted() diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index c25fdaff..714887f5 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -586,11 +586,14 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], - known_failure={"deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL}, note=( "Used to split under `provider` and `local` and was marked a known failure for " "both. Fluent synthesis fixed it outright: rendered standalone this fragment " - "scores 0.986 finished, and cut from the whole sentence it scores 0.019." + "scores 0.986 finished, and cut from the whole sentence it scores 0.019.\n\n" + "The last marker, `deepgram-nova/lexical`, went the same way once holds could be " + "extended on mic energy instead of only on new partials: a text-only detector has " + "no prosody to hold on, so it was expiring mid-pause. Passes 3/3 there now, and " + "the marker was never flagged intermittent, so it had been failing reliably." ), ), Scenario( @@ -826,22 +829,24 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[ContentPreserved(), NoGhostTurns(), NoErrors()], - known_failure={ - "elevenlabs/lexical": "ElevenLabs drops part of the utterance across this gap rather " - "than splitting it — content preserved 1/3" - }, - intermittent=True, note=( "The one scenario whose desired outcome is genuinely ambiguous, so it asserts " "content rather than turn count. At a 3.0s gap both answers are defensible — " "holding costs 3s of dead air, splitting sends a fragment to the LLM — and the " "suite has no basis for calling either wrong. Observed: Flux merges under " "`lexical`/`local` and splits under `heuristic`/`provider`, Nova splits under all " - "four, ElevenLabs merges under `lexical`/`local`. Flux's merge is not Timbal's: " + "four, ElevenLabs splits under `lexical`. Flux's merge is not Timbal's: " "the trace shows Flux streaming partials through the whole gap and emitting one " "commit, so no fragment ever reaches a detector. It previously demanded a merge " "wherever one had been seen, which quietly turned observations into requirements " - "and failed Nova for behaving reasonably." + "and failed Nova for behaving reasonably.\n\n" + "It also carried a known failure blaming ElevenLabs for dropping the second " + "fragment instead of splitting. That was the harness: `AwaitCommit` resolved on " + "the *first* fragment's commit, which on ElevenLabs lands ~1.6s late and so " + "arrived after the wait was armed, leaving only the 0.8s tail for a commit that " + "needed ~1.0s. The turn was lost to teardown, not by the provider — and one " + "observed turn instead of two is also why this note used to say ElevenLabs merged " + "here. It splits, 4/4, content intact." ), ), Scenario( diff --git a/benchmarks/voice/score.py b/benchmarks/voice/score.py index 04cc1c78..ebc6071f 100644 --- a/benchmarks/voice/score.py +++ b/benchmarks/voice/score.py @@ -20,7 +20,7 @@ from pathlib import Path from harness import RunResult -from scenario import Scenario, similarity +from scenario import Scenario, best_window, normalize, similarity HERE = Path(__file__).parent RESULTS_DIR = HERE / "results" @@ -81,14 +81,37 @@ def to_json(self) -> str: return json.dumps(asdict(self)) +# Below this, window matching is not evidence: a one- or two-word needle finds a +# passable window in almost any script, and a spurious lone "I" turn (Flux emits +# them) is a real defect that has to stay countable. +MIN_GHOST_WINDOW_WORDS = 3 + + def count_ghost_turns(result: RunResult, scenario: Scenario, min_similarity: float = 0.6) -> int: - """Committed turns that resemble nothing the script said. + """Committed turns whose content the script never said. Tracked as a metric independent of whether a scenario declared the matching expectation — a hallucinated transcript is worth knowing about everywhere. + + Matched against a *window* of the whole script rather than any single spoken + entry, because turn boundaries are the thing under test and rarely line up + with script boundaries. Comparing per entry mis-scored both directions: a + correct three-fragment merge ("The build fails when I import the module. + Inside a test.") is ~2.5x longer than any fragment of `coding_double_pause` + and resembled none of them, so five cells reported a hallucinated turn for + the merge the scenario asserts — while a run-on split into three commits + counted two ghosts for the same reason inverted. Both were gating. """ spoken = scenario.texts() - return sum(1 for text in result.committed if not any(similarity(text, said) >= min_similarity for said in spoken)) + script = " ".join(spoken) + ghosts = 0 + for text in result.committed: + if len(normalize(text).split()) >= MIN_GHOST_WINDOW_WORDS: + attributable = best_window(script, text) >= min_similarity + else: + attributable = any(similarity(text, said) >= min_similarity for said in spoken) + ghosts += not attributable + return ghosts def record(scenario: Scenario, result: RunResult, repeat: int = 0, jobs: int = 1) -> RunRecord: @@ -175,7 +198,8 @@ class Scorecard: wall_secs: float = 0.0 jobs: int = 1 """Concurrency the cell ran at. Latency gating is suppressed unless this matches - the baseline's — contended runs measure the machine, not the change.""" + the baseline's, so a baseline and its runs must agree; the concurrency itself is + not the problem — see the note in `_compare_latency`.""" def build_scorecard(records: list[RunRecord]) -> Scorecard: @@ -410,9 +434,12 @@ def _compare_timing( if not before or not now: return delta = f"{label} {before:.0f}ms → {now:.0f}ms" - # Concurrent runs share CPU with each other's ONNX inference, so their - # timings measure the machine's load as much as the code's. Comparing - # across different --jobs would gate on scheduling noise. + # Only compare like with like. Measured on deepgram-nova/local, --quick, + # 3 repeats, contention is not detectable at --jobs 6: p50 278ms vs 280ms + # serial, p95 407ms vs 453ms — better, because eou→audio is mostly waiting + # on STT and TTS sockets rather than competing for CPU, and the serial run's + # one 962ms sample is first-run model warmup weighing on a smaller n. The + # guard stays because it is free and the equality is what makes it sound. before_jobs = previous.get("jobs", 1) if card.jobs != before_jobs: out.notes.append(f"{delta} — not gated, measured at --jobs {card.jobs} against a --jobs {before_jobs} baseline") diff --git a/benchmarks/voice/sweep.py b/benchmarks/voice/sweep.py index a5a079d9..1da60a5f 100644 --- a/benchmarks/voice/sweep.py +++ b/benchmarks/voice/sweep.py @@ -1,12 +1,13 @@ -"""Parameter sweep: score a detector setting on merges gained against dead air added. +"""Parameter sweep: score one setting on merges gained against dead air added. -The hold tier is the worked example. ``TEXT_COMPLETE_HOLD_TIMEOUT_SECS`` ships at -0.35s, and it has been measured at exactly two values: 0.35 (splits four +The hold tier is the worked example. ``TEXT_COMPLETE_HOLD_TIMEOUT_SECS`` shipped at +0.35s having been measured at exactly two values: 0.35 (splits four trailing-modifier scenarios) and 3.0 (fixes 11 scenario-cells and adds 2.6s of -dead air to six barge-in cells). Nobody has tried 0.8, or 1.2. The interesting -question — is there a setting that buys most of the merges for a fraction of the -silence — was unanswerable until dead air became measurable, because a -configuration that merged everything by holding forever looked free. +dead air to six barge-in cells). Nobody had tried 0.8, or 1.2 — which is what it +ships at now. The interesting question — is there a setting that buys most of the +merges for a fraction of the silence — was unanswerable until dead air became +measurable, because a configuration that merged everything by holding forever +looked free. Two metrics, deliberately. Optimizing pass rate alone reproduces the mistake this harness was built to catch:: @@ -15,26 +16,36 @@ --param text_complete_hold_timeout_secs --values 0.35,0.8,1.2,2.0,3.0 \\ --stt deepgram-nova,elevenlabs --detector local --repeat 3 +``stt.``-prefixed params vary the provider's own endpointing instead, which is the +other half of the pipeline and the half nobody had tuned:: + + uv run python benchmarks/voice/sweep.py \\ + --param stt.vad_silence_threshold_secs --values 0.4,0.6,0.8,1.2 \\ + --stt elevenlabs --detector local,lexical --repeat 3 + Defaults to the pause-merge family (every scenario asserting ``Merged``), since that is the only family where detectors differ at all — barge-in, plain turns and silence sit at 100% in all twelve cells and would only add runtime and noise. -Results are indicative, not conclusive: 38 English scenarios on three backends, -with ten known failures and real intermittency. Treat a winner as a candidate to -confirm against the full grid and the Flux gate, never as a decision. +Results are indicative, not conclusive: 39 English scenarios on three backends, +18 of them carrying a known failure somewhere, and real intermittency. Treat a +winner as a candidate to confirm against the full grid and the Flux gate, never as +a decision. """ from __future__ import annotations import argparse import asyncio +import logging import statistics as st import sys import time from dataclasses import dataclass, field +import structlog from dotenv import load_dotenv -from harness import HarnessConfig, run_scenario +from harness import HarnessConfig, coerce_param, run_scenario from scenario import SCENARIOS, Merged, Scenario from synth import synthesize_clips, synthesize_fluent @@ -65,20 +76,14 @@ def summary(self) -> str: return f"{self.value:>10} {self.passed:>3}/{self.total:<3} {self.rate:>5.0%} {air}ms {p95}ms" -def _coerce(raw: str) -> float | int | bool | str: - for cast in (int, float): - try: - return cast(raw) - except ValueError: - continue - if raw.lower() in ("true", "false"): - return raw.lower() == "true" - return raw - - async def main() -> int: parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) - parser.add_argument("--param", required=True, help="detector attribute to vary") + parser.add_argument( + "--param", + required=True, + help="attribute to vary: a detector attribute, or 'stt.' for a provider STT knob " + "(see harness.SWEEPABLE_STT_KEYS)", + ) parser.add_argument("--values", required=True, help="comma-separated values to try") parser.add_argument("--stt", default="deepgram-nova,elevenlabs") parser.add_argument("--detector", default="local") @@ -93,7 +98,12 @@ async def main() -> int: parser.add_argument("--jobs", type=int, default=6) args = parser.parse_args() - values = [_coerce(v.strip()) for v in args.values.split(",") if v.strip()] + values = [coerce_param(v.strip()) for v in args.values.split(",") if v.strip()] + param_field, param_key = ( + ("stt_extra", args.param.removeprefix("stt.")) + if args.param.startswith("stt.") + else ("detector_params", args.param) + ) stts = [v.strip() for v in args.stt.split(",") if v.strip()] detectors = [v.strip() for v in args.detector.split(",") if v.strip()] @@ -119,7 +129,7 @@ async def main() -> int: started = time.monotonic() async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: - config = HarnessConfig(stt=stt, detector=det, detector_params={args.param: value}) + config = HarnessConfig(stt=stt, detector=det, **{param_field: {param_key: value}}) async with semaphore: result = await run_scenario(scenario, clips, config) out = outcomes[str(value)] @@ -167,4 +177,9 @@ async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: if __name__ == "__main__": load_dotenv() + # A sweep is hundreds of sessions, and at DEBUG each one emits a few hundred + # lines: the result table lands tens of megabytes below the scroll and gets + # dropped outright by anything that caps captured output. Same default as + # `cli.py`, which had it from the start. + structlog.configure(wrapper_class=structlog.make_filtering_bound_logger(logging.WARNING)) sys.exit(asyncio.run(main())) diff --git a/python/tests/voice/test_session.py b/python/tests/voice/test_session.py index 741f1b83..21768e6a 100644 --- a/python/tests/voice/test_session.py +++ b/python/tests/voice/test_session.py @@ -1559,6 +1559,19 @@ async def close(self) -> None: pass +def _arm_vad(session: VoiceSession, endpointer: object | None) -> None: + """Attach a fake endpointer *and* the evidence flag that gates its use. + + ``_vad_evidence`` is a separate flag set by ``_maybe_start_endpointer`` + only when the detector carries an audio EOU model, because the endpointer + now also arms for text-only detectors that must not inherit the veto + behaviours. Assigning ``_endpointer`` alone therefore exercises the + no-evidence path — which is how three tests here went red unnoticed. + """ + session._endpointer = endpointer # type: ignore[assignment] + session._vad_evidence = endpointer is not None + + class TestVadBargeInVeto: """STT hallucinates plausible phrases from silence (observed live: 'Not, not too bad, mate.' while nobody spoke) — they pass every text gate @@ -1568,16 +1581,16 @@ class TestVadBargeInVeto: def test_veto_matrix(self) -> None: session, _, _ = _make_session() # No endpointer (heuristic mode, no Silero) → never veto. - session._endpointer = None + _arm_vad(session, None) assert session._vad_vetoes_barge_in("no stop that") is False # VAD armed but unhealthy/starved (None) → no evidence, never veto. - session._endpointer = _FakeEndpointer(None) + _arm_vad(session, _FakeEndpointer(None)) assert session._vad_vetoes_barge_in("no stop that") is False # Real speech energy present → allow the barge-in. - session._endpointer = _FakeEndpointer(1.0) + _arm_vad(session, _FakeEndpointer(1.0)) assert session._vad_vetoes_barge_in("no stop that") is False # Armed, healthy, and the mic was silent → hallucination, veto. - session._endpointer = _FakeEndpointer(0.0) + _arm_vad(session, _FakeEndpointer(0.0)) assert session._vad_vetoes_barge_in("no stop that") is True async def _run_barge_in_scenario(self, speech_secs: float | None) -> tuple[VoiceSession, list[VoiceSessionEvent]]: @@ -1590,7 +1603,7 @@ async def _run_barge_in_scenario(self, speech_secs: float | None) -> tuple[Voice tts = SlowMockTTS(delay=0.05, num_chunks=6) tracker = FakePlaybackTracker() session = VoiceSession(agent=agent, stt=stt, tts=tts, playback_tracker=tracker) - session._endpointer = _FakeEndpointer(speech_secs) + _arm_vad(session, _FakeEndpointer(speech_secs)) events: list[VoiceSessionEvent] = [] @@ -1763,7 +1776,7 @@ async def _run_hold_scenario( ) session._hold_partial_grace_secs = grace_secs if endpointer is not None: - session._endpointer = endpointer # type: ignore[assignment] + _arm_vad(session, endpointer) events: list[VoiceSessionEvent] = [] elapsed = 0.0 @@ -1853,6 +1866,39 @@ async def close(self) -> None: f"hold expiry took {elapsed:.2f}s — pre-commit VAD speech stretched the grace" ) + async def test_live_mic_extends_hold_without_any_partial(self) -> None: + """Measured on ElevenLabs at a 0.3s VAD threshold: an interior pause + commits the fragment, then the next fragment's audio is in flight for + over a second before the STT emits a partial for it. Extending only on + partials loses that race and the hold fires mid-sentence, splitting the + utterance — so mic energy alone has to be enough. + """ + + class _LiveSpeechEP: + """Mic is hot *now*; the STT has produced nothing for it yet.""" + + def speech_secs_in_window(self, window_secs: float) -> float: # noqa: ARG002 + return 0.5 + + def notify_committed(self) -> None: + return None + + async def close(self) -> None: + return None + + elapsed, _ = await self._run_hold_scenario( + grace_secs=2.0, + timeout_secs=0.2, + partial_after_commit_delay=None, + endpointer=_LiveSpeechEP(), + ) + # Speech never stops, so the extension runs to its cap and no further: + # unbounded, the assistant's own echo could hold a turn open forever. + assert elapsed > 1.0, f"hold expired after {elapsed:.2f}s while the mic was live" + assert elapsed < VoiceSession.HOLD_VAD_MAX_EXTENSION_SECS + 1.5, ( + f"hold ran {elapsed:.2f}s — the extension cap is not holding" + ) + async def test_dangling_token_hold_is_dropped_on_expiry(self) -> None: """Live bug: stale-force-committed \"I\" HOLDs for 3s then becomes a user turn and the LLM invents a reply. Dangling tokens must die here.""" diff --git a/python/tests/voice/test_turn_detection.py b/python/tests/voice/test_turn_detection.py index daa643b8..8c48c545 100644 --- a/python/tests/voice/test_turn_detection.py +++ b/python/tests/voice/test_turn_detection.py @@ -478,11 +478,12 @@ async def test_late_barge_in_on_finished_turn_not_held(self) -> None: async def test_incomplete_audio_complete_text_short_hold(self) -> None: """Confidence tier: Smart Turn under-scores short closers ("Thank you." - p=0.036 live) — terminal punctuation disagrees, so the hold shrinks to - the short tier instead of eating the full budget as dead air. + p=0.036 live) — terminal punctuation disagrees, so the hold shrinks + below the full budget instead of eating all of it as dead air. - Keep this well under the incomplete-text HOLD (1.2s): VAD has usually - already waited, and a second 1.2s tax is the cold-start "slow" feel. + The tier was 0.35s until the sweep retuned it to 1.2s, which is also + what the incomplete-text tier costs: the two now differ only in the + logged reason, and "short" means short of ``hold_timeout_secs`` alone. """ det = LocalAudioTurnDetector(audio_eou=_FixedAudioEou(0.1)) await det.start(type("C", (), {"sample_rate": 16000})()) @@ -491,8 +492,8 @@ async def test_incomplete_audio_complete_text_short_hold(self) -> None: assert decision.action is CommitAction.HOLD assert decision.reason == "audio_hold_text_complete" assert decision.hold_timeout_secs == det.text_complete_hold_timeout_secs - assert det.text_complete_hold_timeout_secs == 0.35 - assert det.text_complete_hold_timeout_secs < det.text_incomplete_hold_timeout_secs + assert det.text_complete_hold_timeout_secs == 1.2 + assert det.text_complete_hold_timeout_secs <= det.text_incomplete_hold_timeout_secs assert det.text_complete_hold_timeout_secs < det.hold_timeout_secs # Per-session clones keep the knob. assert det.clone().text_complete_hold_timeout_secs == det.text_complete_hold_timeout_secs diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index ae0fb923..62c4a842 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -920,6 +920,48 @@ def _vad_confirms_speech_since(self, since_monotonic: float) -> bool: speech_secs = self._endpointer.speech_secs_in_window(window) return speech_secs is not None and speech_secs >= self.MIN_BARGE_IN_VAD_SPEECH_SECS + # Trailing window for "the user is still talking right now". Long enough to + # bridge Silero's between-phoneme dips, short enough that a HOLD fires + # promptly once they really stop. + HOLD_VAD_SPEECH_WINDOW_SECS = 0.5 + MIN_HOLD_VAD_SPEECH_SECS = 0.1 + # Ceiling on how long mic energy alone may defer one HOLD. Echo surviving an + # imperfect canceller carries energy, so without a cap the assistant's own + # playback could hold a turn open for as long as it speaks. + HOLD_VAD_MAX_EXTENSION_SECS = 3.0 + + def _vad_hears_speech_now(self, since_monotonic: float) -> bool: + """Silero saw speech in the last :attr:`HOLD_VAD_SPEECH_WINDOW_SECS`, + counting only after ``since_monotonic``. + + Two departures from the neighbouring VAD gates, both because this one + *triggers* a hold extension instead of corroborating an STT partial: + + Missing evidence returns ``False``, not ``True`` — a permissive default + would defer every hold to its cap on any session without Silero. + + It does not require :attr:`_vad_evidence` (an audio EOU model). That + flag guards behaviours that can *suppress* something the user did, like + vetoing a barge-in, where being wrong makes the assistant + uninterruptible. Declining to end a turn while the mic is live only + delays it, by at most :attr:`HOLD_VAD_MAX_EXTENSION_SECS`, and the + user's own commit supersedes the hold either way — and the text-only + detectors that lack an audio EOU are exactly the ones whose STT splits + utterances soonest. + + The anchor matters only for holds shorter than the window: no shipped + tier is (1.2s is the shortest, and the provider's own silence threshold + precedes it), but without it a 0.2s hold would count the held + utterance's own tail as the user resuming and extend on itself. + """ + if self._endpointer is None: + return False + window = min(self.HOLD_VAD_SPEECH_WINDOW_SECS, time.monotonic() - since_monotonic) + if window <= 0: + return False + speech_secs = self._endpointer.speech_secs_in_window(window) + return speech_secs is not None and speech_secs >= self.MIN_HOLD_VAD_SPEECH_SECS + # -- Internal: audio → STT --------------------------------------------- async def _forward_audio(self, audio_in: AsyncIterable[bytes]) -> None: @@ -1078,6 +1120,7 @@ async def _expire() -> None: me = asyncio.current_task() try: remaining = timeout_secs + vad_extended_secs = 0.0 while True: await asyncio.sleep(remaining) # Never fire mid-utterance: a *new* STT partial since the @@ -1099,6 +1142,26 @@ async def _expire() -> None: timeout_secs=timeout_secs, ) continue + # Mic says the user is still going but the STT has not caught + # up. Waiting for a partial loses this race whenever the + # provider commits on a short silence: measured on + # ElevenLabs at a 0.3s VAD threshold, an interior pause + # committed the fragment and the next one's audio was in + # flight ~1.3s before any partial existed to extend on, so + # a 1.2s hold fired mid-sentence and split the utterance. + if vad_extended_secs < self.HOLD_VAD_MAX_EXTENSION_SECS and self._vad_hears_speech_now(anchor): + remaining = min( + self.HOLD_VAD_SPEECH_WINDOW_SECS, + self.HOLD_VAD_MAX_EXTENSION_SECS - vad_extended_secs, + ) + vad_extended_secs += remaining + logger.debug( + "stt_hold_extended_vad", + remaining=round(remaining, 3), + extended_secs=round(vad_extended_secs, 3), + timeout_secs=timeout_secs, + ) + continue break except asyncio.CancelledError: return From 315020e506f7cd5ee1ae8fa89f42ab511e11ad8a Mon Sep 17 00:00:00 2001 From: berges99 Date: Sun, 26 Jul 2026 23:36:50 +0200 Subject: [PATCH 12/30] fix(voice): rescue stranded transcripts when the mic goes quiet MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The stale-partial watchdog exists to force a commit when a provider transcribes speech and then never commits it — the live failure where the words hang as a "…" caption forever. It measured staleness from the last partial arrival, which a provider that hallucinates on trailing silence refreshes indefinitely: ElevenLabs emits invented partials 1.0-1.2s apart against a 2.5s threshold, so the same churn that stops it committing kept our rescue permanently disarmed. The user's interruption was lost outright in 8 of 12 barge-in runs. Mic silence now counts as well: if Silero heard essentially nothing in the window, the user demonstrably stopped speaking and the provider clearly will not commit, whatever it is still emitting. Measured 4/12 -> 15/24 on the ElevenLabs barge-ins with no session errors, and clean across 156 runs on the four baselined Deepgram cells. Not gated on _vad_evidence: that flag guards inferences which can suppress shing the user did, and this only rescues speech that would otherwise be lost. Two alternatives measured worse and are documented so they are not retried: commit_strategy="manual" (0/12, every run erroring on assistant audio) and dropping the synthesis fallback's text-stability requirement (4/12, and it synthesized a hallucinated "Yeah." as a turn). Tests cover both directions — churning partials over a quiet mic must rescue, a hot mic must still defer — the first verified to fail on the old anchor. Also drops the README's claim that --update-baseline refuses --jobs > 1, which is no longer true. --- benchmarks/voice/README.md | 55 +++++++++++++++++++++------- python/tests/voice/test_session.py | 57 ++++++++++++++++++++++++++++++ python/timbal/voice/session.py | 44 +++++++++++++++++++++-- 3 files changed, 141 insertions(+), 15 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 49197697..b3aa40a3 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -687,17 +687,46 @@ present — and then never commits: Not the harness, and not the hold change: forcing the waits back to resolving immediately reproduces it identically, 0/3, and the same scenario passes 3/3 on `deepgram-nova/lexical` while ElevenLabs passes 4/4 on non-barge-in scenarios. The -plausible mechanism is visible in the trace — ElevenLabs hallucinates on the -trailing silence, and with `commit_strategy="vad"` each invented partial restarts -the 1.2s silence timer that would otherwise commit, so the real utterance is held -open indefinitely. That is the same threshold the merge rates depend on, which -makes it a poor thing to be load-bearing twice. +mechanism is visible in the trace — ElevenLabs hallucinates on the trailing +silence, and with `commit_strategy="vad"` each invented partial restarts the 1.2s +silence timer that would otherwise commit, so the real utterance is held open +indefinitely. That is the same threshold the merge rates depend on, which makes it +a poor thing to be load-bearing twice. + +**But calling it provider-side was letting Timbal off too easily.** The session +already has a watchdog for precisely this — a partial the provider never commits, +whose docstring describes the words hanging "as a '…' caption forever" and which is +meant to fire once "the provider clearly won't". It measured staleness from the +*last partial arrival*, so partials landing 1.0–1.2s apart against its 2.5s +threshold kept it permanently disarmed: the churn that stops ElevenLabs committing +is the same churn that stops the safety net noticing. Logging the anchor shows it +firing at `stale_secs` of 0.0, 0.4 and 0.9 once mic silence counts too — three +rescues that could never have happened on transcript staleness alone. + +Anchoring on mic silence instead (`_mic_quiet_for`: Silero heard ≤0.1s of speech in +the window, so the user demonstrably stopped, whatever the provider is still +emitting) takes the four barge-in scenarios from 4/12 to **15/24**, no session +errors, with the three remaining failures flaky rather than hard and +`support_barge_in_instant` passing outright. It is deliberately not gated on +`_vad_evidence`: that flag guards inferences which can *suppress* something the +user did, and this one only rescues speech that would otherwise be lost. Confirmed +free of collateral damage across 156 runs on the four baselined Deepgram cells — no +unexpected failures, no errors, and the single ghost is `banking_confirmation` on +`deepgram-flux/local`, which produced the identical ghost in 1 of 3 repeats before +the change. + +Two fixes that looked obvious and measured worse, both worth not re-trying: + +| Hypothesis | Result | +|---|---| +| `commit_strategy="manual"`, so Timbal drives commits instead of ElevenLabs' VAD | **0/12**, and every run also errored `timed out waiting for assistant audio`. The first turn still commits via the endpointer, but the reply never arrives in time. Only viable at all where the endpointer arms — under `heuristic` or `provider` nothing would ever commit. | +| Dropping the synthesis fallback's requirement that the partial text hold still across its 400ms grace, since a hallucination landing inside that window skips the rescue | **4/12** and it synthesized a hallucinated `"Yeah."` as a turn of its own. The stability check is not merely guarding against a racing commit: it is the only thing separating real speech from churn. A stranded turn beats an invented one. | Consequence for the baseline: 5 of 12 cells carry a current one, all Deepgram, all at `--jobs 6`. The two ElevenLabs entries are stale — `--jobs 1`, ~31 runs from a -`--quick` subset — and cannot be refreshed while the provider is dropping turns, -since a cell with unmarked failures is refused. Latency there is consequently -ungated on a concurrency mismatch as well. +`--quick` subset — and still cannot be refreshed, since a cell with unmarked +failures is refused and the barge-ins remain flaky at 62%. Latency there is +consequently ungated on a concurrency mismatch as well. Two incidental findings from the same session. `sweep.py` never configured structlog, so every sweep — including the tier retune above — buried its own @@ -792,11 +821,11 @@ failures that are the STT's alone and land identically under all four detectors, like Nova committing a "mm-hmm"; writing those per cell states one fact four times and hides that it is one fact. -`--jobs N` overlaps runs across the whole queue, cells included. Two rules keep it -from corrupting the thing it accelerates: `--update-baseline` is refused above -`--jobs 1`, and latency is never compared across differing concurrency — it is -printed with a note instead. Pass rates and ghost turns still gate normally, so a -parallel matrix run is a real gate on everything except speed. +`--jobs N` overlaps runs across the whole queue, cells included. One rule keeps it +from corrupting the thing it accelerates: latency is never compared across differing +concurrency — it is printed with a note instead. Baselines may be taken in parallel +(see the measurement above), so what a parallel run records is gated against later +runs at the same `--jobs`. Pass rates and ghost turns gate regardless. ## Results and the regression gate diff --git a/python/tests/voice/test_session.py b/python/tests/voice/test_session.py index 21768e6a..79a7204c 100644 --- a/python/tests/voice/test_session.py +++ b/python/tests/voice/test_session.py @@ -2064,3 +2064,60 @@ async def _run() -> None: assert session.transcript[0].role == "user" assert session.transcript[0].text == "What are you doing?" + + async def _run_churn_scenario(self, endpointer: object) -> tuple[_StuckPartialSTT, VoiceSession]: + """Stranded partial while the provider keeps emitting *new* partials + faster than the stale threshold, so transcript staleness never accrues. + """ + agent = Agent(name="t", model=TestModel(responses=["ok"]), tools=[]) + stt = _StuckPartialSTT() + session = VoiceSession(agent=agent, stt=stt, tts=MockTTS()) + session._stale_partial_poll_secs = 0.05 + session._stale_partial_commit_secs = 0.4 + _arm_vad(session, endpointer) + + events: list[VoiceSessionEvent] = [] + + async def _empty_audio() -> AsyncIterator[bytes]: + return + yield # noqa: RET504 + + async def _drive() -> None: + while not any(isinstance(e, SessionStarted) for e in events): + await asyncio.sleep(0.01) + stt.pending_text = "Sorry, one more thing." + # 0.1s apart against a 0.4s threshold: every hallucination resets the + # anchor well before it can expire. + for text in ("Sorry, one more thing.", "Yeah.", "I don't know.", "Yeah.", "Mm.", "Yeah."): + await stt.inject(TranscriptEvent(type="partial", text=text)) + await asyncio.sleep(0.1) + await stt.finish() + + async def _run() -> None: + async with aclosing(session.run(_empty_audio())) as stream: + driver = asyncio.create_task(_drive()) + async for ev in stream: + events.append(ev) + await driver + + await asyncio.wait_for(_run(), timeout=10) + return stt, session + + async def test_partial_churn_does_not_disarm_sweeper(self) -> None: + """Measured on ElevenLabs barge-ins: it hallucinates on trailing silence, + and each invented partial both restarts its own VAD silence timer (so it + never commits) and refreshes this sweeper's anchor (so the rescue never + fires). The user's interruption was lost outright in 8 of 12 runs. A quiet + mic has to be enough to conclude the provider is not going to commit. + """ + stt, session = await self._run_churn_scenario(_FakeEndpointer(0.0)) + assert stt.commit_calls >= 1, "churning partials kept the sweeper disarmed" + assert any(e.role == "user" and e.text == "Sorry, one more thing." for e in session.transcript) + + async def test_live_mic_still_defers_the_sweeper(self) -> None: + """The mirror of the above: partials arriving while the mic is genuinely + hot mean the user is still talking, and force-committing there would cut + them off mid-utterance. Only *silence* may substitute for staleness. + """ + stt, _ = await self._run_churn_scenario(_FakeEndpointer(0.5)) + assert stt.commit_calls == 0, "sweeper force-committed while the user was still speaking" diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index 62c4a842..63f5d885 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -962,6 +962,28 @@ def _vad_hears_speech_now(self, since_monotonic: float) -> bool: speech_secs = self._endpointer.speech_secs_in_window(window) return speech_secs is not None and speech_secs >= self.MIN_HOLD_VAD_SPEECH_SECS + # Silero speech inside a window that still counts as quiet. A stray frame or + # two is a blip on breath or a click rather than the user resuming, and + # demanding exactly zero would let one of them keep a stranded transcript + # hostage for as long as the session lives. + MAX_QUIET_SPEECH_SECS = 0.1 + + def _mic_quiet_for(self, secs: float) -> bool: + """Silero heard essentially nothing in the trailing ``secs``. + + Missing evidence returns ``False`` — no Silero means no opinion, and the + caller falls back to transcript staleness. + + Not gated on :attr:`_vad_evidence`, for the reason + :meth:`_vad_hears_speech_now` is not: that flag guards inferences which + can *suppress* something the user did. This one only rescues speech that + would otherwise be lost outright. + """ + if self._endpointer is None: + return False + speech_secs = self._endpointer.speech_secs_in_window(secs) + return speech_secs is not None and speech_secs <= self.MAX_QUIET_SPEECH_SECS + # -- Internal: audio → STT --------------------------------------------- async def _forward_audio(self, audio_in: AsyncIterable[bytes]) -> None: @@ -991,6 +1013,16 @@ async def _sweep_stale_partials(self) -> None: force ``stt.commit()`` so the transcript flows through the normal ``_handle_committed`` path. + A *newer partial* is the wrong thing to wait on by itself. ElevenLabs + hallucinates on trailing silence, and each invented partial both restarts + its own VAD silence timer — so it never commits — and refreshes this + watchdog's anchor, so the safety net stays disarmed by the very churn it + exists to catch. Measured on `medical_barge_in`: partials 1.0-1.2s apart + (``"Sorry, one more thing."``, ``"Yeah."``, ``"Yeah."``) against a 2.5s + threshold, and the interrupting turn was never committed at all. So mic + silence counts too: if the user demonstrably stopped speaking that long + ago, the provider clearly will not commit, whatever it is still emitting. + Providers whose ``commit()`` is a no-op (Deepgram Flux) never answer that nudge. After a short grace for Finalize-capable providers, we synthesize a committed event from the stranded partial text so the @@ -1009,13 +1041,14 @@ async def _sweep_stale_partials(self) -> None: if self._last_partial_at <= self._stale_commit_sent_at: continue stale_secs = time.monotonic() - self._last_partial_at - if stale_secs < self._stale_partial_commit_secs: + mic_quiet = self._mic_quiet_for(self._stale_partial_commit_secs) + if stale_secs < self._stale_partial_commit_secs and not mic_quiet: continue self._stale_commit_sent_at = time.monotonic() stranded = self._latest_partial_text # INFO on purpose: this is the only trace that a transcript was # rescued from a provider that silently refused to commit. - logger.info("stt_stale_partial_commit", stale_secs=round(stale_secs, 1)) + logger.info("stt_stale_partial_commit", stale_secs=round(stale_secs, 1), mic_quiet=mic_quiet) try: await self.stt.commit() except Exception as e: @@ -1024,6 +1057,13 @@ async def _sweep_stale_partials(self) -> None: await asyncio.sleep(0.4) if self._closed or not stranded: continue + # The text holding still across the grace is load-bearing, and not + # merely a guard against racing a mid-flight commit: it is the + # only thing separating real speech from provider churn. Dropping + # it (so a partial that mutated inside the 400ms still synthesized) + # was measured at 4/12 on the ElevenLabs barge-ins versus 7/12 + # with it, and synthesized a hallucinated ``"Yeah."`` as a turn of + # its own. A stranded turn is better than an invented one. if self._latest_partial_text == stranded and self._last_partial_at > self._last_commit_at: logger.info( "stt_stale_partial_synthesized", From 403d4fd3e068843cf1f76bd724ece7a6cf49c618 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 00:17:02 +0200 Subject: [PATCH 13/30] fix(voice): score echo against a same-length window of the assistant's speech _likely_stt_echo compared a commit against a tail sized at 3x its length. ratio() is 2M/(len(c)+len(tail)), so that capped the score at 0.50 against a 0.68 threshold: the fuzzy branch was unreachable and a perfect echo scored below it. Only exact substrings were ever suppressed, which is why echo the STT garbled slightly walked through the filter built to catch it. Score against a slice of the tail the commit's own length instead, aligned on their longest shared run. Threshold calibrated on transcripts from --aec-leak runs: garbled echo scores 0.68-1.00, genuine barge-ins 0.24-0.58, and 0.65 sits in the gap nearer the echo side, since over-suppression makes the assistant uninterruptible. At leak 0.15 the gated suite goes 92% -> 100% with ghost turns halved; the four baselined clean cells stay at 100% over 126 runs. Also makes --aec-leak a real axis. Cells were matched to records by rebuilding "stt/detector", so any run with a leak or a swept param matched no cell at all: no scorecard, no gating, and --update-baseline silently did nothing. Records now carry the full label and the leak gain. --- benchmarks/voice/README.md | 56 ++++++++++++++++ benchmarks/voice/cli.py | 19 ++++-- benchmarks/voice/scenario.py | 78 +++++++++++++++++++++-- benchmarks/voice/score.py | 30 +++++++-- python/tests/voice/test_turn_detection.py | 49 ++++++++++++++ python/timbal/voice/turn_detection.py | 33 +++++++++- 6 files changed, 250 insertions(+), 15 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index b3aa40a3..6e1920cd 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -61,6 +61,62 @@ which inverts the intuition that louder bleed is the dangerous case. That also explains why the boundary is probabilistic rather than a threshold: it depends on how the STT happens to mis-hear a given phrase, not on the gain alone. +**The "clean at 0.15" row above is an artifact of measuring one scenario.** The +leak axis had only ever been run against `support_echo_silence`; running the whole +suite at 0.15 on `deepgram-flux/local` gives 57/78 with **12 ghost turns and 9 +scenarios failing**, every one of them `interrupted=True` with a fragment of the +assistant's own reply committed as a user turn — `'Add memory access.'` from "a bad +memory access", `'exactly once.'`, `'retailers. Stop.'`, `'Hopefully, you should see +a doctor.'`. `support_simple` — a single question, one reply, no pauses — has the +assistant interrupting itself on 3 of 4 repeats. So a merely mediocre echo canceller +does not degrade turn-taking at the margins; it breaks the ordinary case, and the +suite's clean bill of health came entirely from never having fed it echo. + +**Fixed by comparing against a length-matched window.** The cap above is entirely an +artifact of scoring a short commit against a long tail, so the repair is to score it +against a slice of the tail its own length, aligned on the longest run the two share: + +```python +block = SequenceMatcher(None, c, tail).find_longest_match(0, len(c), 0, len(tail)) +start = max(0, min(len(tail) - len(c), block.b - block.a)) +return SequenceMatcher(None, c, tail[start : start + len(c)]).ratio() >= 0.65 +``` + +Anchoring beats sliding every window, which is the obvious alternative and measurably +worse: a weak anchor yields a badly-matched window, so coincidental resemblance +elsewhere in the reply cannot inflate the score. On the adversarial case it is the +difference between 0.75 and 0.58. The threshold is calibrated on transcripts from leak +runs rather than picked — garbled echo of a known reply scores 0.68–1.00 and genuine +barge-ins against the same replies score 0.24–0.58, two classes that do not overlap — +and 0.65 sits in that gap nearer the echo side deliberately, since suppressing real +speech makes the assistant uninterruptible, the worse of the two failures. + +| | before | after | +|---|---|---| +| leak 0.15, gated | 44/48 and 55/60 (~92%) | **40/40 (100%)** | +| leak 0.15, ghost turns | 12 per 78 runs | **6** | +| clean, 4 baselined cells | 100% | **100%, no regressions** (126 runs) | + +The clean-run check is the one that matters for shipping it: a suppressor that catches +more echo can start eating genuine interruptions, and `support_barge_in`, +`medical_barge_in` and friends all still barge in. + +**The residual has a separate cause worth its own fix.** Both call sites gate the check +behind `state.assistant_active`, so echo that commits just *after* playback ends is +never tested at all. `coding_followup_after_reply` is the clean demonstration: it +commits `'memory access.'`, which is an exact substring of its own reply "a segfault +means bad memory access" and would be caught by the very first branch — but the reply +has finished by the time it lands, so nothing looks. Any fix needs a short grace window +after playback rather than dropping the flag, or a user turn that legitimately echoes +the last reply becomes unsuppressable. + +Both mechanisms that consume mic energy were ruled out as causes by disabling them: +the hold's VAD extension (`HOLD_VAD_MAX_EXTENSION_SECS = 0`) and the stale-partial +watchdog's mic-quiet anchor, separately and together, fail at the same rate. That +matters because both look like plausible suspects — echo carries energy, so in +principle it can defer a hold and can go quiet in a way that triggers a rescue — and +neither is responsible. The under-suppression is the whole story. + **The fuzzy branch of that check is unreachable, provably.** `_likely_stt_echo` falls back to `SequenceMatcher(c, tail).ratio() >= 0.68`, where `tail` is `max(3*len(c), 100)` characters. Since `ratio()` is `2M/(len(c)+len(tail))` with diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index 1b316c44..59b2ec41 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -119,10 +119,16 @@ def _list_scenarios() -> int: for detector, reason in s.known_failure.items(): kind = "intermittent" if s.intermittent else "known failure" print(f" [{kind}, {detector}] {reason}") + for detector, reason in s.known_failure_under_leak.items(): + print(f" [under --aec-leak, {detector}] {reason}") if s.note: print(f" {s.note}") known = sum(1 for s in SCENARIOS if s.known_failure) - print(f"\n{len(SCENARIOS)} scenarios, {known} known failures; * = --quick subset") + leak_known = sum(1 for s in SCENARIOS if s.known_failure_under_leak) + print( + f"\n{len(SCENARIOS)} scenarios, {known} known failures, " + f"{leak_known} more under --aec-leak; * = --quick subset" + ) return 0 @@ -256,13 +262,16 @@ def log(kind: str, detail: str = "") -> None: print(line) if live else buffer.append(line) result = await run_scenario(job.scenario, clips, job.config, log=log) - known = job.scenario.known_failure_reason(job.config.detector, job.config.stt) - report = _report(result, known, job.scenario.intermittent) + leak = job.config.aec_leak + known = job.scenario.known_failure_reason(job.config.detector, job.config.stt, leak) + report = _report(result, known, job.scenario.is_intermittent(job.config.detector, job.config.stt, leak)) if live: print("\n".join(report)) else: print("\n".join([job.header, *buffer, *report])) - return record(job.scenario, result, repeat=job.repeat, jobs=jobs) + return record( + job.scenario, result, repeat=job.repeat, jobs=jobs, aec_leak=leak, label=job.config.label + ) records = list(await asyncio.gather(*(run(job) for job in queue))) @@ -277,7 +286,7 @@ def log(kind: str, detail: str = "") -> None: exit_code = 0 for config in cells: - cell_records = [r for r in records if f"{r.stt}/{r.detector}" == config.label] + cell_records = [r for r in records if r.label == config.label] if not cell_records: continue card = build_scorecard(cell_records) diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 714887f5..5c84a751 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -407,6 +407,18 @@ class Scenario: *desired* expectations stay in the file rather than being rewritten to match broken behavior. If it starts passing, that's reported as an unexpected pass. """ + known_failure_under_leak: dict[str, str] = field(default_factory=dict) + """Same key grammar, but only when the run injects echo (``--aec-leak`` > 0). + + Echo is a separate axis, not a harder version of the clean one: a scenario can + be sound under user-only audio and fail purely because the assistant hears + itself. Folding the two into one table would either excuse a clean-run failure + or make every leak run report nine regressions it already knows about. + + Always treated as intermittent, whatever :attr:`intermittent` says, because + under-suppression depends on how the STT happens to mis-hear a given phrase + rather than on the gain — so a pass at any single gain proves nothing. + """ intermittent: bool = False """The known failure is nondeterministic, so passing sometimes means nothing. @@ -438,9 +450,18 @@ def _scoped(self, table: dict[str, Any], detector: str, stt: str | None) -> Any def expectations_for(self, detector: str, stt: str | None = None) -> list[Expectation]: return self._scoped(self.expect_by_detector, detector, stt) or self.expect - def known_failure_reason(self, detector: str, stt: str | None = None) -> str | None: + def known_failure_reason(self, detector: str, stt: str | None = None, aec_leak: float = 0.0) -> str | None: + """The leak table wins when echo is injected: it is the more specific claim, + and a scenario marked for both is failing for two different reasons.""" + if aec_leak and (hit := self._scoped(self.known_failure_under_leak, detector, stt)) is not None: + return hit return self._scoped(self.known_failure, detector, stt) + def is_intermittent(self, detector: str, stt: str | None = None, aec_leak: float = 0.0) -> bool: + if aec_leak and self._scoped(self.known_failure_under_leak, detector, stt) is not None: + return True + return self.intermittent + def applies_to(self, detector: str) -> bool: return self.detectors is None or detector in self.detectors @@ -553,6 +574,30 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "one; not specific to this scenario" ) +# Every leak failure in the suite is one bug wearing nine hats: the assistant hears +# its own bleed, interrupts itself, and commits a fragment of its own reply as a user +# turn — 'Add memory access.' from "a bad memory access", 'retailers. Stop.' from +# "...authorized retailers." `_likely_stt_echo` is a text-similarity check whose fuzzy +# branch is provably unreachable (the tail is sized at 3x the commit, capping +# SequenceMatcher at 0.50 against a 0.68 threshold), so only exact substrings are +# caught and echo the STT garbles walks straight through the filter built for it. +# +# Scoped to the one cell the leak axis has actually been measured on. The suppressor +# is shared code, so the other eleven are presumably no better — but "presumably" is +# what these markers exist to keep out, and an unmeasured cell should report its +# failures rather than have them excused by a Flux observation. +# +# The set of scenarios carrying this is empirical and incomplete by construction: which +# ones trip depends on how the STT garbles a given reply, so successive runs surface +# different members. It reached thirteen by two samples at 0.15 and would likely grow +# with repeats. The leak *baseline* is the real instrument — it records per-scenario +# rates and gates on movement — and these markers exist so one can be taken at all. +_ECHO_UNDER_SUPPRESSION = ( + "the assistant interrupts itself on its own echo: bleed transcribed badly enough stops " + "resembling its source and passes `_likely_stt_echo`" +) +_ECHO_LEAK_CELL = "deepgram-flux/local" + _PROVIDER_ENDPOINTING_FAILURE = ( "`provider` defers to Flux's endpointing, which splits here; `lexical` merges it " "correctly because Namo scores the fragment 0.00 incomplete" @@ -571,6 +616,13 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: script=[Say("What's your return policy?"), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], quick=True, + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, + note=( + "One question, one reply, no pauses — and at a 0.15 echo leak the assistant " + "interrupts itself on 3 of 4 repeats. The simplest scenario in the suite is enough " + "to show that a mediocre echo canceller does not degrade turn-taking at the " + "margins, it breaks the ordinary case." + ), ), Scenario( id="support_pause", @@ -586,6 +638,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "Used to split under `provider` and `local` and was marked a known failure for " "both. Fluent synthesis fixed it outright: rendered standalone this fragment " @@ -602,6 +655,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: replies=["Happy to help. Have a good day."], script=[Say("That's all."), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), MaxDeadAir(3500), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "The case the text-complete hold tier exists for, and the only one in the suite: " "Smart Turn under-scores this closer (0.115 — 13 of 14 closers measured score " @@ -655,6 +709,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(), NoErrors(), ], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note="Pairs with support_barge_in: same reply, later offset, measurably longer heard text.", ), Scenario( @@ -685,6 +740,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), Interrupted(True), NoGhostTurns(), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "The most important barge-in in voice UX and the one the code is built to ignore: " "both HeuristicTurnDetector and ProviderTurnDetector drop partials shorter than " @@ -755,16 +811,21 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Silence(4.0), ], expect=[UserTurns(1), Interrupted(False), NoGhostTurns(), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "Run with --aec-leak to bleed the assistant's output back into the mic. " "`_likely_stt_echo` exists so speaker bleed does not make the assistant " "interrupt itself, and until this scenario nothing had ever fed it echo: every " "run was clean user-only audio. coding_barge_in_echo proves the suppressor does " "not fire on genuine speech; this is the other half.\n\n" - "Measured on deepgram-flux/local: clean at 0.0 and 0.15, intermittent from 0.20, " - "and 4 failures in 6 at 0.30 — where the assistant cuts itself off mid-reply and " - "commits its own words as a user turn. Real barge-in still works at 0.30, so the " - "suppressor is letting echo through rather than over-suppressing.\n\n" + "Measured on deepgram-flux/local: clean at 0.0, intermittent from 0.20, and 4-5 " + "failures in 6 at 0.30 — where the assistant cuts itself off mid-reply and commits " + "its own words as a user turn. Real barge-in still works at 0.30, so the suppressor " + "is letting echo through rather than over-suppressing.\n\n" + "0.15 was recorded as clean here and is not: it fails ~1 in 3. The original reading " + "came from too few repeats on the one scenario the leak axis was ever run against. " + "Running the whole suite at 0.15 fails nine scenarios, which is why the marker now " + "lives on all of them rather than here alone.\n\n" "The mechanism is visible in what gets committed: 'Our retailers.', 'Arise " "retailers.', 'has aroused retailers.' — all manglings of the reply's own tail, " "'...authorized retailers.' The suppressor is a text-similarity check against " @@ -792,6 +853,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: replies=["One large coffee and a croissant. Anything else?"], script=[Say("Can I get a large coffee and a croissant?"), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, ), Scenario( id="food_pause", @@ -811,6 +873,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL + " — merged 2/3", }, + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, intermittent=True, quick=True, note=( @@ -957,6 +1020,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], expect=[UserTurns(2), NoGhostTurns(), NoErrors()], known_failure={"elevenlabs/*": _EL_OVERMERGE}, + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "The inverse of every pause scenario: two genuinely finished sentences separated by " "a short gap, which must *not* merge. The suite is full of cases punishing a split " @@ -1024,6 +1088,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(3), Interrupted(True), NoGhostTurns(), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "Two interruptions in one session. Every other barge-in scenario stops after the " "first, so nothing checked that the session recovers enough to be interrupted " @@ -1117,6 +1182,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: # look like a hallucinated turn to every text comparison. script=[Say("My account number is four four seven two nine one."), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note="Digit strings are the STT-hostile case: no lexical context to fall back on.", ), Scenario( @@ -1280,6 +1346,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), Interrupted(True), NoGhostTurns(min_similarity=0.5), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "A real interruption made of words the assistant is in the middle of saying, which " "is what asking someone to repeat themselves sounds like. `_likely_stt_echo` " @@ -1330,6 +1397,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), Interrupted(False), NoGhostTurns(), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "A second turn taken after the assistant has finished speaking, uninterrupted. " "This is a regression test for a bug we shipped: STT not resuming once the " diff --git a/benchmarks/voice/score.py b/benchmarks/voice/score.py index ebc6071f..ea7d7b3b 100644 --- a/benchmarks/voice/score.py +++ b/benchmarks/voice/score.py @@ -68,6 +68,18 @@ class RunRecord: jobs: int = 1 """Concurrency this run was measured under. Latency is only comparable at equal concurrency, so it is recorded per run rather than inferred later.""" + aec_leak: float = 0.0 + """Echo gain fed back into the mic. Recorded because it changes what the run means + — a leak run and a clean one were previously indistinguishable in the JSONL, so a + file could only be read correctly by whoever remembered the command.""" + label: str = "" + """Full cell label, axis suffixes included (``[leak=0.15]``, swept params). + + Scoring and baselining key off this rather than rebuilding ``stt/detector``, which + silently dropped every non-default axis: a leak or sweep run matched no cell at + all, so it printed no scorecard, gated nothing, and its ``--update-baseline`` was + a no-op. Once matched, the same stripping would have let a leak cell overwrite the + clean baseline of the same stt/detector.""" @property def xfail(self) -> bool: @@ -114,7 +126,14 @@ def count_ghost_turns(result: RunResult, scenario: Scenario, min_similarity: flo return ghosts -def record(scenario: Scenario, result: RunResult, repeat: int = 0, jobs: int = 1) -> RunRecord: +def record( + scenario: Scenario, + result: RunResult, + repeat: int = 0, + jobs: int = 1, + aec_leak: float = 0.0, + label: str = "", +) -> RunRecord: return RunRecord( scenario=scenario.id, domain=scenario.domain, @@ -132,9 +151,11 @@ def record(scenario: Scenario, result: RunResult, repeat: int = 0, jobs: int = 1 vad_endpointed=[m.vad_endpointed for m in result.metrics], errors=list(result.errors), wall_secs=round(result.wall_secs, 2), - known_failure=scenario.known_failure_reason(result.detector, result.stt) or "", - intermittent=scenario.intermittent, + known_failure=scenario.known_failure_reason(result.detector, result.stt, aec_leak) or "", + intermittent=scenario.is_intermittent(result.detector, result.stt, aec_leak), jobs=jobs, + aec_leak=aec_leak, + label=label or f"{result.stt}/{result.detector}", ) @@ -218,7 +239,8 @@ def build_scorecard(records: list[RunRecord]) -> Scorecard: passed = sum(r.passed for r in gated) return Scorecard( - label=f"{records[0].stt}/{records[0].detector}", + # Fallback keeps result files written before labels were recorded scoreable. + label=records[0].label or f"{records[0].stt}/{records[0].detector}", stt=records[0].stt, detector=records[0].detector, runs=len(gated), diff --git a/python/tests/voice/test_turn_detection.py b/python/tests/voice/test_turn_detection.py index 8c48c545..3e8129cd 100644 --- a/python/tests/voice/test_turn_detection.py +++ b/python/tests/voice/test_turn_detection.py @@ -28,11 +28,60 @@ TurnState, _is_garbage_commit, _is_same_user_utterance_refinement, + _likely_stt_echo, resolve_turn_detector, ) from .test_session import MockSTT, MockTTS + +class TestLikelySttEcho: + """Garbled echo must be suppressed; genuine speech against the same reply must not. + + Both lists are real transcripts from ``--aec-leak`` runs, so this pins the margin + the threshold was calibrated on rather than restating the implementation. + """ + + REPLY = ( + "Our return policy allows returns within thirty days of purchase, provided " + "the item is unused and you still have the original receipt or a valid proof " + "of purchase from one of our authorized retailers." + ) + SEGFAULT_REPLY = "A segfault means bad memory access." + + def test_garbled_echo_is_suppressed(self) -> None: + """The old check scored these 0.23-0.33 against a 0.68 threshold and passed + every one through: it compared the commit to a tail sized at 3x its length, + which caps ratio() at 0.50, so the branch could never fire.""" + for echo in ( + "Our retailers.", + "Arise retailers.", + "Advised retailers.", + "advertised retailers.", + "Archives to retailers.", + "has aroused retailers.", + ): + assert _likely_stt_echo(echo, self.REPLY), echo + + def test_genuine_barge_ins_survive(self) -> None: + for real in ("Actually, cancel that.", "Wait, hold on.", "Okay, never mind.", "Okay, thanks."): + assert not _likely_stt_echo(real, self.REPLY), real + + def test_user_quoting_the_assistant_survives(self) -> None: + """The tightest case in the suite (`coding_barge_in_echo`): the user repeats the + assistant's own words, which is what asking someone to clarify sounds like. It + scores 0.58 against echo's 0.68 floor — the whole margin, so it guards it.""" + reply = "Python caches imported modules, so the module body runs exactly once." + assert not _likely_stt_echo("Sorry, the module cache?", reply) + assert _likely_stt_echo("When look exactly once.", reply) + + def test_exact_substring_still_suppressed(self) -> None: + assert _likely_stt_echo("memory access.", self.SEGFAULT_REPLY) + + def test_no_assistant_text_is_never_echo(self) -> None: + assert not _likely_stt_echo("Our retailers.", "") + + # --------------------------------------------------------------------------- # Moved heuristic functions (ported from test_voice_session_stt_refinement.py) # --------------------------------------------------------------------------- diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index 0d7e993c..be622d73 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -228,6 +228,22 @@ def _normalize_echo(s: str) -> str: return " ".join(s.lower().split()) +# Similarity between a commit and the best-aligned same-length window of the +# assistant's recent speech, above which the commit is treated as echo. +# +# Calibrated on transcripts from `--aec-leak` runs, not chosen: garbled echo of a +# known reply scores 0.68-1.00 ("archives to retailers." / "advised retailers." / +# "add memory access.") and genuine barge-ins against the same replies score +# 0.24-0.58 ("wait, hold on." 0.43, "stop." 0.40). The two classes do not overlap, +# and 0.65 sits in the gap nearer the echo side on purpose: suppressing real speech +# makes the assistant uninterruptible, which is the worse failure of the two. +# +# The tightest case is `coding_barge_in_echo` at 0.58, where the user quotes the +# assistant's own words back ("sorry, the module cache?") — genuinely ambiguous from +# text alone, and the scenario exists to keep that margin honest. +_ECHO_WINDOW_RATIO = 0.65 + + def _likely_stt_echo(committed: str, assistant_so_far: str) -> bool: """True if STT text is probably the assistant's own speech leaking into the mic.""" c = _normalize_echo(committed) @@ -243,7 +259,22 @@ def _likely_stt_echo(committed: str, assistant_so_far: str) -> bool: return True tail_len = min(len(a), max(len(c) * 3, 100)) tail = a[-tail_len:] - return SequenceMatcher(None, c, tail).ratio() >= 0.68 + if len(tail) <= len(c): + return SequenceMatcher(None, c, tail).ratio() >= _ECHO_WINDOW_RATIO + # Compare against a *same-length* window of the tail, aligned on the longest run + # the two share. Scoring against the whole tail cannot work: ratio() is + # 2M/(len(c)+len(tail)) with M <= len(c), and the tail is deliberately sized at + # 3x the commit, which caps the score at 0.50 — so a perfect echo scored below + # the old 0.68 threshold and this branch was unreachable. Only exact substrings + # were ever suppressed, which is precisely why echo the STT garbles slightly + # walked through the filter built to catch it. Anchoring also beats sliding every + # window: a weak anchor yields a badly-matched window, so coincidental + # resemblance elsewhere in the reply cannot inflate the score. + block = SequenceMatcher(None, c, tail).find_longest_match(0, len(c), 0, len(tail)) + if not block.size: + return False + start = max(0, min(len(tail) - len(c), block.b - block.a)) + return SequenceMatcher(None, c, tail[start : start + len(c)]).ratio() >= _ECHO_WINDOW_RATIO def _is_same_user_utterance_refinement(active: str, new: str) -> bool: From 7dafbd4f93981a7222a027227dd34bd33a2fa200 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 00:28:25 +0200 Subject: [PATCH 14/30] fix(bench): stop gating aggregates on filtered runs Per-scenario pass rates are matched by name, so they stay comparable under -s / --quick. Ghost turns, latency and dead air are not: each is computed over whatever subset ran, so comparing them against a full-suite baseline compares two different populations. This is not theoretical. Running the barge-in subset to check the new echo threshold reported "ghost turns 1 -> 3" while the cell was clean, because those eight scenarios carry most of the suite's ghost turns. The other direction is worse: a subset that excludes them reports an improvement just as falsely, and an improvement is not something anyone goes looking behind. compare() now takes `partial` and reports the aggregates as not comparable, which is the reasoning that already makes --update-baseline refuse a filtered run. Also records the cross-cell validation of the echo threshold from 403d4fd3. All seven baselined cells were run. deepgram-flux/provider is the decisive one, since _likely_stt_echo is the only semantic filter between a partial and cancelling the reply there: 53/54, with all ten barge-in scenarios passing every repeat and support_echo_silence still uninterrupted. ElevenLabs' 17/24 and 21/24 are its documented hallucination on trailing silence ('Yes.', 'Yeah.'), not over-suppression -- the genuine barge-in is heard in every one. --- benchmarks/voice/README.md | 24 ++++++++++++++++++++++-- benchmarks/voice/cli.py | 2 +- benchmarks/voice/score.py | 20 ++++++++++++++++++-- 3 files changed, 41 insertions(+), 5 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 6e1920cd..6511ef10 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -98,8 +98,28 @@ speech makes the assistant uninterruptible, the worse of the two failures. | clean, 4 baselined cells | 100% | **100%, no regressions** (126 runs) | The clean-run check is the one that matters for shipping it: a suppressor that catches -more echo can start eating genuine interruptions, and `support_barge_in`, -`medical_barge_in` and friends all still barge in. +more echo can start eating genuine interruptions. All seven baselined cells were run, +and the decisive one is `deepgram-flux/provider`, where `_likely_stt_echo` is the *only* +semantic filter between a partial and cancelling the reply — no VAD corroboration, no +EOU, nothing to catch an over-suppression. It scores 53/54 with all ten barge-in +scenarios passing every repeat, `coding_barge_in_echo` included, while +`support_echo_silence` stays uninterrupted. Its one flake is `food_long_pause` with +`interrupted=False`, so the assistant never spoke over it and the echo check was never +consulted. + +The ElevenLabs cells look worse (17/24 and 21/24 on the barge-in subset) and are not: +the genuine barge-in is heard, and the extra turn is `'Yes.'` or `'Yeah.'` — the +provider's documented hallucination on trailing silence, the same family as the `'Bye.'` +above. 17/24 is also up from the 15/24 measured there before this change. + +Reading that comparison surfaced a gate defect worth knowing about. Per-scenario rates +are matched by name and safe on a filtered run, but ghost turns, latency and dead air +are aggregates over whatever subset ran, so comparing them against a full-suite +baseline compares populations. The barge-in subset alone carries most of the suite's +ghost turns and duly reported "ghost turns 1 → 3" while being clean; a subset that +*excludes* them would have reported an improvement just as falsely. `compare()` now +takes `partial` and skips aggregates for filtered runs, which is the same reasoning +that already makes `--update-baseline` refuse them. **The residual has a separate cause worth its own fix.** Both call sites gate the check behind `state.assistant_active`, so echo that commits just *after* playback ends is diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index 59b2ec41..4cbb2962 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -312,7 +312,7 @@ def log(kind: str, detail: str = "") -> None: print(f" baseline updated for {card.label}") continue - comparison = compare(card, baseline) + comparison = compare(card, baseline, partial=bool(args.scenario or args.quick)) for line in comparison.notes: print(f"\n note: {line}") if comparison.improvements: diff --git a/benchmarks/voice/score.py b/benchmarks/voice/score.py index ea7d7b3b..340bdd93 100644 --- a/benchmarks/voice/score.py +++ b/benchmarks/voice/score.py @@ -402,8 +402,18 @@ def ok(self) -> bool: return not self.regressions -def compare(card: Scorecard, baseline: dict[str, dict]) -> Comparison: - """Gate on movement away from the baseline, not on absolute thresholds.""" +def compare(card: Scorecard, baseline: dict[str, dict], partial: bool = False) -> Comparison: + """Gate on movement away from the baseline, not on absolute thresholds. + + ``partial`` marks a filtered run (``-s`` / ``--quick``). Per-scenario rates stay + comparable because they are matched by name, but every *aggregate* is computed over + a different population than the baseline's, so comparing them invents movement that + is only a change of subject. Measured: the barge-in subset alone carries most of the + suite's ghost turns, so running just those reported "ghost turns 1 → 3" against a + full-suite baseline while being clean — and the reverse is worse, since a subset + that excludes them looks like an improvement. Latency and dead air are the same + story, a p50 over eight scenarios against a p50 over thirty-nine. + """ out = Comparison() previous = baseline.get(card.label) if previous is None: @@ -427,6 +437,12 @@ def compare(card: Scorecard, baseline: dict[str, dict]) -> Comparison: for name in card.unexpected_passes: out.improvements.append(f"{name}: known failure now passes — drop the known_failure marker") + if partial: + out.notes.append( + "filtered run: per-scenario rates gated, aggregates (ghost turns, latency, dead air) not comparable" + ) + return out + if card.ghost_turns > previous.get("ghost_turns", 0): out.regressions.append(f"ghost turns {previous.get('ghost_turns', 0)} → {card.ghost_turns}") From 1b54c6259c01cf69b3c37525b71577f1c4356466 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 09:12:44 +0200 Subject: [PATCH 15/30] fix(voice): stop the watchdog resurrecting echo the suppressor rejected MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Echo that commits just after playback was never checked: both call sites gated on assistant_active, which drops when playback drains while the transcript for that audio is still in flight. TurnState now carries seconds_since_assistant_active and the check runs 2s past playback. Bounded because assistant_text outlives its turn — with no deadline, a user utterance resembling the last reply would be dropped, and dropping it means no new turn starts to clear that text, so the suppression would never lift. That alone fixed nothing. Tracing coding_followup_after_reply showed the suppressor refusing 'memory access.' as echo, then the stale-partial watchdog synthesizing it into a turn three seconds later: an IGNOREd commit does not bump _last_commit_at, so suppressed echo still looks stranded. The watchdog exists to rescue user speech an over-eager AEC ducked below the provider's commit threshold, which is the one thing echo is not, sit now runs the same check before rescuing. coding_followup_after_reply 0/3 -> 3/3; ghost turns across the 78-run leak suite 12 -> 2. Clean cells unmoved: flux/local, flux/lexical and nova/local at 100%, flux/provider and nova/lexical each losing only the pre-existing food_long_pause flake. Retires eleven of the thirteen leak markers. support_barge_in_one_word keeps one for a different reason: the STT merges the echo tail and the user's word into a single commit ('retailers. Stop.'), so suppression and admission are one decision over two utterances. --- benchmarks/voice/README.md | 60 +++++++++++++++++++++++---- benchmarks/voice/scenario.py | 49 ++++++++-------------- python/timbal/voice/session.py | 30 +++++++++++++- python/timbal/voice/turn_detection.py | 39 ++++++++++++++++- 4 files changed, 135 insertions(+), 43 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 6511ef10..5a517b9a 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -121,14 +121,58 @@ ghost turns and duly reported "ghost turns 1 → 3" while being clean; a subset takes `partial` and skips aggregates for filtered runs, which is the same reasoning that already makes `--update-baseline` refuse them. -**The residual has a separate cause worth its own fix.** Both call sites gate the check -behind `state.assistant_active`, so echo that commits just *after* playback ends is -never tested at all. `coding_followup_after_reply` is the clean demonstration: it -commits `'memory access.'`, which is an exact substring of its own reply "a segfault -means bad memory access" and would be caught by the very first branch — but the reply -has finished by the time it lands, so nothing looks. Any fix needs a short grace window -after playback rather than dropping the flag, or a user turn that legitimately echoes -the last reply becomes unsuppressable. +**The residual had two causes, and the second was self-inflicted.** Both call sites +gated the check behind `state.assistant_active`, so echo committing just *after* +playback ended was never tested. `coding_followup_after_reply` was the clean +demonstration: it commits `'memory access.'`, an exact substring of its own reply, and +nothing looks. `TurnState` now carries `seconds_since_assistant_active` and the check +runs for 2s past playback — bounded, because `assistant_text` outlives its turn, so an +unbounded window would let a user utterance resembling the last reply be dropped, and +dropping it means no new turn starts to clear that text. + +That alone fixed nothing, which is the interesting part. Tracing the scenario showed the +suppressor working perfectly and the rescue path undoing it: + +``` +stt_committed_received 'memory access.' audio_playing=True +stt_commit_ignored reason=echo <- suppressed correctly +stt_stale_partial_commit mic_quiet=True stale_secs=1.9 +stt_stale_partial_synthesized 'memory access.' <- resurrected 3s later +stt_committed_accepted action=new_turn <- ghost turn +``` + +An IGNOREd commit does not bump `_last_commit_at`, so suppressed echo still looks like a +stranded partial to the stale-partial watchdog, which synthesizes it back once the grace +window has closed. The watchdog exists to rescue user speech that an over-eager AEC +ducked below the provider's commit threshold — which is the one thing echo is not — so +it now runs the same echo check before rescuing. Together: `coding_followup_after_reply` +0/3 → 3/3, and ghost turns across the whole 78-run leak suite 12 → 2. + +Worth noting the shape of this bug, since the codebase invites more of it: two fixes +that are individually correct, landed a day apart, in different files, that cancel each +other. Neither test suite could catch it because each mechanism is right in isolation. + +| leak 0.15, deepgram-flux/local | ghosts (78 runs) | `coding_followup_after_reply` | +| --- | --- | --- | +| before the suppressor fix | 12 | 0/2 | +| window-anchored suppressor | 6 | 0/3 | +| \+ grace window | 6 | 0/3 | +| \+ rescue guard | **2** | **3/3** | + +Eleven of the thirteen leak markers were retired by this. The two that remain are +different in kind: `support_barge_in_one_word` gets the echo tail and the user's word in +a *single* commit (`'retailers. Stop.'`), so suppressing it loses the barge-in the +scenario tests — that needs the echo span located inside the commit, not a verdict on +the whole string. + +**The axis still will not baseline, and the refusal is the finding.** At `--repeat 3` it +scores 94% with all six failures flaky — `banking_digits_pause`, `coding_barge_in`, +`food_simple`, `medical_barge_in_twice`, each passing some repeats — plus three session +timeouts. Which scenarios trip depends on how the STT happens to garble a given reply, +so successive runs surface different members and a marker set fitted to one run is +fitted to noise. Two samples of the suite are not enough to tell a 90%-reliable scenario +from a broken one; that needs repeats in the tens, which is the next real step here +rather than more marker churn. Both mechanisms that consume mic energy were ruled out as causes by disabling them: the hold's VAD extension (`HOLD_VAD_MAX_EXTENSION_SECS = 0`) and the stale-partial diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 5c84a751..8789fb0d 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -574,27 +574,24 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "one; not specific to this scenario" ) -# Every leak failure in the suite is one bug wearing nine hats: the assistant hears -# its own bleed, interrupts itself, and commits a fragment of its own reply as a user -# turn — 'Add memory access.' from "a bad memory access", 'retailers. Stop.' from -# "...authorized retailers." `_likely_stt_echo` is a text-similarity check whose fuzzy -# branch is provably unreachable (the tail is sized at 3x the commit, capping -# SequenceMatcher at 0.50 against a 0.68 threshold), so only exact substrings are -# caught and echo the STT garbles walks straight through the filter built for it. +# What survives echo suppression once the suppressor actually works. # -# Scoped to the one cell the leak axis has actually been measured on. The suppressor -# is shared code, so the other eleven are presumably no better — but "presumably" is -# what these markers exist to keep out, and an unmeasured cell should report its -# failures rather than have them excused by a Flux observation. +# Thirteen scenarios carried this marker when the leak axis first ran, all failing the +# same way: the assistant heard its own bleed, interrupted itself, and committed a +# fragment of its own reply. Eleven were retired by fixing `_likely_stt_echo` to score +# against a same-length window, and the twelfth by refusing to let the stale-partial +# watchdog resurrect a commit that had already been suppressed as echo. # -# The set of scenarios carrying this is empirical and incomplete by construction: which -# ones trip depends on how the STT garbles a given reply, so successive runs surface -# different members. It reached thirteen by two samples at 0.15 and would likely grow -# with repeats. The leak *baseline* is the real instrument — it records per-scenario -# rates and gates on movement — and these markers exist so one can be taken at all. -_ECHO_UNDER_SUPPRESSION = ( - "the assistant interrupts itself on its own echo: bleed transcribed badly enough stops " - "resembling its source and passes `_likely_stt_echo`" +# This one is different in kind and will not yield to a better threshold. The STT hands +# over a *single* commit containing both the echo tail and the user's real word — +# "retailers. Stop." out of "...authorized retailers." plus "Stop." — so suppression and +# admission are the same decision applied to two utterances. Dropping it loses the +# interruption the scenario exists to test; keeping it scores a ghost turn. Splitting +# the commit is the only real fix, and that needs the echo span located within it +# rather than a verdict on the whole string. +_ECHO_MIXED_COMMIT = ( + "the STT merges the echo tail and the user's word into one commit " + "('retailers. Stop.'), so it cannot be suppressed without losing the barge-in" ) _ECHO_LEAK_CELL = "deepgram-flux/local" @@ -616,7 +613,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: script=[Say("What's your return policy?"), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], quick=True, - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "One question, one reply, no pauses — and at a 0.15 echo leak the assistant " "interrupts itself on 3 of 4 repeats. The simplest scenario in the suite is enough " @@ -638,7 +634,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "Used to split under `provider` and `local` and was marked a known failure for " "both. Fluent synthesis fixed it outright: rendered standalone this fragment " @@ -655,7 +650,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: replies=["Happy to help. Have a good day."], script=[Say("That's all."), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), MaxDeadAir(3500), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "The case the text-complete hold tier exists for, and the only one in the suite: " "Smart Turn under-scores this closer (0.115 — 13 of 14 closers measured score " @@ -709,7 +703,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoGhostTurns(), NoErrors(), ], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note="Pairs with support_barge_in: same reply, later offset, measurably longer heard text.", ), Scenario( @@ -740,7 +733,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), Interrupted(True), NoGhostTurns(), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_MIXED_COMMIT}, note=( "The most important barge-in in voice UX and the one the code is built to ignore: " "both HeuristicTurnDetector and ProviderTurnDetector drop partials shorter than " @@ -811,7 +804,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Silence(4.0), ], expect=[UserTurns(1), Interrupted(False), NoGhostTurns(), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "Run with --aec-leak to bleed the assistant's output back into the mic. " "`_likely_stt_echo` exists so speaker bleed does not make the assistant " @@ -853,7 +845,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: replies=["One large coffee and a croissant. Anything else?"], script=[Say("Can I get a large coffee and a croissant?"), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, ), Scenario( id="food_pause", @@ -873,7 +864,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL + " — merged 2/3", }, - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, intermittent=True, quick=True, note=( @@ -1020,7 +1010,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], expect=[UserTurns(2), NoGhostTurns(), NoErrors()], known_failure={"elevenlabs/*": _EL_OVERMERGE}, - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "The inverse of every pause scenario: two genuinely finished sentences separated by " "a short gap, which must *not* merge. The suite is full of cases punishing a split " @@ -1088,7 +1077,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(3), Interrupted(True), NoGhostTurns(), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "Two interruptions in one session. Every other barge-in scenario stops after the " "first, so nothing checked that the session recovers enough to be interrupted " @@ -1182,7 +1170,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: # look like a hallucinated turn to every text comparison. script=[Say("My account number is four four seven two nine one."), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note="Digit strings are the STT-hostile case: no lexical context to fall back on.", ), Scenario( @@ -1346,7 +1333,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), Interrupted(True), NoGhostTurns(min_similarity=0.5), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "A real interruption made of words the assistant is in the middle of saying, which " "is what asking someone to repeat themselves sounds like. `_likely_stt_echo` " @@ -1397,7 +1383,6 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: *_SETTLE, ], expect=[UserTurns(2), Interrupted(False), NoGhostTurns(), NoErrors()], - known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_UNDER_SUPPRESSION}, note=( "A second turn taken after the assistant has finished speaking, uninterrupted. " "This is a regression test for a bug we shipped: STT not resuming once the " diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index 63f5d885..2df7fe5f 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -43,6 +43,7 @@ TurnDetector, TurnState, _is_same_user_utterance_refinement, + _likely_stt_echo, resolve_turn_detector, ) @@ -454,6 +455,13 @@ def __init__( # Assistant text accumulated during the in-flight turn (for STT echo suppression). self._turn_assistant_text: str = "" + # Last time the assistant was observed speaking, for the echo grace window. + # Sampled rather than hooked because `_assistant_active` is derived from + # playback draining, which has no event to hang a callback on. Every partial + # and commit samples it, and echo is exactly what produces partials, so the + # reading is dense when it matters. A stale sample can only over-state the + # elapsed time and close the window early, which is the safe direction. + self._last_assistant_active_at: float = 0.0 # User text for the in-flight turn. Streaming STT (e.g. ElevenLabs VAD) often # emits a second ``committed_transcript`` that extends the first; without this, @@ -1044,6 +1052,20 @@ async def _sweep_stale_partials(self) -> None: mic_quiet = self._mic_quiet_for(self._stale_partial_commit_secs) if stale_secs < self._stale_partial_commit_secs and not mic_quiet: continue + # Never rescue the assistant's own voice. An IGNOREd commit does + # not bump _last_commit_at, so suppressed echo still looks like a + # stranded partial — and this path is where it comes back to life: + # traced under --aec-leak, "memory access." was refused as echo + # while the reply played, then synthesized into a turn of its own + # three seconds later. Nothing downstream catches it, because by + # then the detector's echo grace window has closed. + # + # This rescue exists for user speech an over-eager AEC ducked + # below the provider's commit threshold, which is the one thing + # echo is not. + if _likely_stt_echo(self._latest_partial_text, self._turn_assistant_text): + logger.debug("stt_stale_partial_echo_skipped", text_preview=self._latest_partial_text[:80]) + continue self._stale_commit_sent_at = time.monotonic() stranded = self._latest_partial_text # INFO on purpose: this is the only trace that a transcript was @@ -1127,13 +1149,19 @@ def _turn_state(self) -> TurnState: # so the next commit can refine/merge against it — but do NOT fold HOLD # into assistant_active (that breaks hallucination filters + refinements). active = self._held_user_text if holding else self._active_turn_user_text + assistant_active = self._assistant_active + if assistant_active: + self._last_assistant_active_at = now return TurnState( - assistant_active=self._assistant_active, + assistant_active=assistant_active, audio_playing=self._assistant_audio_playing, assistant_text=self._turn_assistant_text, active_user_text=active, seconds_since_turn_start=now - self._turn_started_at, seconds_since_last_commit=now - self._last_commit_at, + seconds_since_assistant_active=( + None if assistant_active or not self._last_assistant_active_at else now - self._last_assistant_active_at + ), partials_since_last_commit=self._partials_since_last_commit, holding=holding, ) diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index be622d73..09a230da 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -70,6 +70,12 @@ class TurnState(BaseModel): """User text of the in-flight turn, or the pending HOLD fragment when holding.""" seconds_since_turn_start: float seconds_since_last_commit: float + seconds_since_assistant_active: float | None = None + """Seconds since the assistant was last speaking, or ``None`` while it still is. + + ``None`` also covers "has never spoken", so a detector must treat it as "no echo + is possible" rather than "long ago". + """ partials_since_last_commit: int """Partial transcripts seen since the previous committed transcript.""" holding: bool = False @@ -244,6 +250,35 @@ def _normalize_echo(s: str) -> str: _ECHO_WINDOW_RATIO = 0.65 +# How long after the assistant stops speaking its echo may still arrive. +# +# STT commits lag the audio that produced them — ~0.3s of endpointing on Deepgram +# Flux, ~1.6s on ElevenLabs — so the tail of a reply routinely commits after playback +# has already drained. 2s covers both with margin. +_ECHO_GRACE_SECS = 2.0 + + +def _echo_window_open(state: TurnState) -> bool: + """The assistant is speaking, or stopped recently enough that echo is still landing. + + Gating the echo check on :attr:`TurnState.assistant_active` alone misses precisely + the leak that arrives last, because the flag drops when playback drains while the + transcript for that audio is still in flight. Measured under ``--aec-leak``: + `coding_followup_after_reply` commits ``"memory access."`` — an exact substring of + its own reply, which the first branch of :func:`_likely_stt_echo` would catch — and + nothing looks, so it becomes a ghost turn. + + Bounded rather than left open until the next turn, because ``assistant_text`` + outlives the turn that produced it. Without a deadline a user whose genuine + utterance resembled the last reply would have it dropped — and dropping it means no + new turn starts to clear that text, so the suppression would never lift. + """ + if state.assistant_active: + return True + since = state.seconds_since_assistant_active + return since is not None and since <= _ECHO_GRACE_SECS + + def _likely_stt_echo(committed: str, assistant_so_far: str) -> bool: """True if STT text is probably the assistant's own speech leaking into the mic.""" c = _normalize_echo(committed) @@ -421,7 +456,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: and not state.holding ): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination") - if state.assistant_active and _likely_stt_echo(text, state.assistant_text): + if _echo_window_open(state) and _likely_stt_echo(text, state.assistant_text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") # Pending HOLD: STT often re-commits a longer form of the same fragment. # Mid-turn "refinement" IGNORE would freeze the held text until timeout — @@ -562,7 +597,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: return CommitDecision(action=CommitAction.IGNORE, text=text, reason="garbage") if _is_hesitation_only(text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hesitation") - if state.assistant_active and _likely_stt_echo(text, state.assistant_text): + if _echo_window_open(state) and _likely_stt_echo(text, state.assistant_text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") return CommitDecision(action=CommitAction.NEW_TURN, text=text, reason="provider") From 5ecf89c73e108c07107df4285a2d12861029ebec Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 09:42:00 +0200 Subject: [PATCH 16/30] fix(voice): keep provider churn from destroying the stranded utterance MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Two changes, both aimed at ElevenLabs' habit of inventing stock phrases on trailing silence, which cost the barge-in scenarios real turns. A hallucinated "Yeah." overwrote _latest_partial_text and refreshed the staleness anchor, so the user's actual words were both gone and un-rescuable — the same churn that stops the provider committing also disarms the watchdog built to catch that. A partial is now ignored for those two purposes when a stranded partial is already waiting, the new text is not that one refined, and Silero heard nothing recent. All three are required: silence alone would break the watchdog's founding case, where the user speaks quietly under playback and neither the provider VAD nor Silero registers it. The detector still sees the text; deciding whether to interrupt on it belongs to _vad_vetoes_barge_in. The harness had the larger share. settle_secs was a flat 1.0s against a shortest hold tier of 1.2s, so quiesnce could not distinguish a finished session from one deliberately debouncing, and runs were torn down mid-hold: 'Sorry, one more thing.' commits as a 1.5s lexical_hold and the run ends before it fires, scoring as the product losing a turn. Now derived from the detector's own hold timeouts, because getting it wrong is invisible and looks like someone else's bug — as it did here, where these failures were previously recorded as provider variance. Four EL barge-in scenarios 15/24 -> 24/24 with no ghost turns. Full suite on cells that could not previously be baselined: elevenlabs/local 61/62, elevenlabs/lexical 63/66, zero session errors. Deepgram unmoved, and the pause family is 16/16 under the longer settle. --- benchmarks/voice/README.md | 30 ++++++++++++++++++++++++ benchmarks/voice/harness.py | 39 ++++++++++++++++++++++++++---- python/timbal/voice/session.py | 43 +++++++++++++++++++++++++++++++++- 3 files changed, 107 insertions(+), 5 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 5a517b9a..444b939b 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -835,6 +835,36 @@ unexpected failures, no errors, and the single ghost is `banking_confirmation` o `deepgram-flux/local`, which produced the identical ghost in 1 of 3 repeats before the change. +**Most of the remainder turned out to be this harness, not the provider.** Two further +changes took the same four scenarios from 15/24 to **24/24** with zero ghost turns, and +the second is the one that mattered. + +The first keeps the churn from destroying what the watchdog exists to rescue. A +hallucinated `"Yeah."` overwrote `_latest_partial_text` and refreshed the staleness +anchor, so the real utterance was both gone and un-rescuable; a partial is now ignored +for those two purposes when a stranded partial is already waiting, the new text is not +that one refined, and Silero heard nothing recent. All three conditions are needed — +silence alone would break the watchdog's founding case, where the user speaks quietly +under playback and neither the provider VAD nor Silero registers it. Worth 19/24 alone. + +The second: `settle_secs` was a flat 1.0s, and the shortest HOLD tier is 1.2s. A hold +emits nothing while it debounces — that is the entire point of it — so a quiescence rule +shorter than the hold cannot distinguish "finished" from "deliberately waiting", and the +harness tore down mid-hold. The trace is unambiguous: `'Sorry, one more thing.'` commits +as a 1.5s `lexical_hold` and the run ends before it can fire, scoring as the product +losing a turn. It is now derived from the detector's own hold timeouts (`local` 3.5s, +`lexical` 2.0s, the holdless detectors 1.0s) rather than chosen, because the failure +mode of getting it wrong is invisible and looks like someone else's bug. + +That correction is worth stating plainly: the five failures written off above as +provider variance were substantially mine. The A/B that appeared to exonerate the wait +changes only compared *whether* a wait resolved, not whether it resolved early, and a +settle that fires mid-hold resolves perfectly happily. Full suite after both, previously +unbaselinable: `elevenlabs/local` 61/62, `elevenlabs/lexical` 63/66, no session errors on +either. Deepgram is unmoved — `flux/lexical` 34/34, `flux/provider` at its usual 26/27, +and the pause family that stood to lose most from a longer settle is 16/16 across +`support_pause`, `support_pause_short`, `food_long_pause` and `coding_double_pause`. + Two fixes that looked obvious and measured worse, both worth not re-trying: | Hypothesis | Result | diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index b6b1004b..167011fd 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -340,6 +340,40 @@ def _build_detector(config: HarnessConfig) -> Any: return detector +def _settle_secs(config: HarnessConfig) -> float: + """How long the session must say nothing before a wait accepts what it has. + + Must exceed the longest HOLD the detector can arm, and this is the whole reason + the value is derived rather than chosen. A hold emits nothing while it debounces + — that is what it is for — so a quiescence rule shorter than the hold cannot tell + "the session is finished" from "the session is deliberately waiting", and the + harness tears down mid-hold. It reads as the *product* dropping a turn. + + Measured on the ElevenLabs barge-ins, where the interrupting utterance commits as + a 1.5s `lexical_hold` against a flat 1.0s settle: 19/24 at 1.0s, 24/24 once the + settle clears the hold. Those five were previously written off as provider + flakiness, which is what a harness bug looks like from the outside when it only + bites the slowest provider. + + Floors at 1.0s to cover the gap between speech ending and the first partial for + it (~0.4s on ElevenLabs, the slowest measured here) on detectors that never hold. + """ + detector = resolve_turn_detector(_build_detector(config)) + holds = [ + getattr(detector, name, None) + # DEFAULT_ included because LexicalTurnDetector passes its class constant + # straight into the decision without ever binding an instance attribute. + for name in ( + "hold_timeout_secs", + "DEFAULT_HOLD_TIMEOUT_SECS", + "text_complete_hold_timeout_secs", + "text_incomplete_hold_timeout_secs", + ) + ] + longest = max((h for h in holds if isinstance(h, int | float)), default=0.0) + return max(1.0, longest + 0.5) + + async def run_scenario( scenario: Scenario, clips: dict[str, bytes], @@ -397,10 +431,7 @@ async def wait_for(predicate, timeout: float, what: str) -> None: return await asyncio.sleep(FRAME_SECS) - # How long the session must say nothing before a wait accepts what it already - # has. Wide enough to cover the gap between speech ending and the first - # partial for it (~0.4s on ElevenLabs, the slowest measured here). - settle_secs = 1.0 + settle_secs = _settle_secs(config) def _settled(events: list[float], after: float) -> bool: """Whether the session is done with the speech fed up to ``after``. diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index 2df7fe5f..12d2a542 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -976,6 +976,39 @@ def _vad_hears_speech_now(self, since_monotonic: float) -> bool: # hostage for as long as the session lives. MAX_QUIET_SPEECH_SECS = 0.1 + # Trailing window Silero must find quiet before a partial can be called invented. + # Shorter than the barge-in window because this fires between utterances, where + # the pause is the signal, not during one. + HALLUCINATION_QUIET_WINDOW_SECS = 0.5 + + def _partial_clobbers_stranded(self, text: str) -> bool: + """A partial that is neither the stranded utterance refined nor backed by mic energy. + + ElevenLabs invents stock phrases on trailing silence — ``"Yeah."``, ``"Yes."``, + ``"I don't know."`` — and each one costs twice over. It overwrites the real + utterance the watchdog would have rescued, and it refreshes the staleness anchor + so the watchdog stays disarmed by the very churn it exists to catch. The + provider's own VAD silence timer restarts too, so the real words never commit by + either route: measured on `medical_barge_in`, the interrupting turn was never + committed by anyone. + + Deliberately narrow, because silence alone does not make a partial invented. The + watchdog exists for the user who speaks quietly under playback, where an + over-eager AEC ducks the mic and *neither* the provider VAD nor Silero registers + an utterance — refusing every uncorroborated partial would break the case the + thing was built for. So all three must hold: a stranded partial is already + waiting, the new text is not that one refined, and Silero heard nothing recent. + + The detector still sees the text; only the rescue payload and its anchor are + protected. Deciding whether to interrupt on it is + :meth:`_vad_vetoes_barge_in`'s job, and it applies a stricter standard. + """ + if not self._latest_partial_text or self._last_partial_at <= self._last_commit_at: + return False + if _is_same_user_utterance_refinement(self._latest_partial_text, text): + return False + return self._mic_quiet_for(self.HALLUCINATION_QUIET_WINDOW_SECS) + def _mic_quiet_for(self, secs: float) -> bool: """Silero heard essentially nothing in the trailing ``secs``. @@ -1103,7 +1136,15 @@ async def _process_stt_events(self) -> None: if event.type == "partial": text = event.text.strip() self._partials_since_last_commit += 1 - if text: + if text and self._partial_clobbers_stranded(text): + # INFO on purpose: this is the only trace that a real + # utterance was kept alive against provider churn. + logger.info( + "stt_partial_hallucination_ignored", + text_preview=text[:80], + stranded_preview=self._latest_partial_text[:80], + ) + elif text: self._last_partial_at = time.monotonic() self._latest_partial_text = text decision = await self.turn_detector.on_partial(text, self._turn_state()) From e55bad531bc548684154e7f2257d40828a19dcde Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 11:00:44 +0200 Subject: [PATCH 17/30] fix(voice): gate echo resemblance on proof, and suppress unvoiced commits MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The echo suppressor was dropping genuine user speech. `food_long_pause` on elevenlabs/lexical went 4/4 -> 0/4: "Pepperoni pizza, please." after a reply of "Got it — a large pepperoni pizza." scores 0.67 against the resemblance check and gets suppressed, on a clean run where no echo exists. The threshold was calibrated only on barge-ins, where the user changes the subject; confirmations, disambiguation and digit readback put the user's next words into the reply by design, and there the two populations interleave (0.67/0.78 genuine against 0.76/0.79 echo). No threshold separates them. Split the check accordingly. A verbatim substring of what is playing is evidence and always counts. Garbled resemblance is a guess, and only runs once the same session has produced verbatim echo. That trades leak suppression back (leak 0.15: ~100% with 13 markers -> 85% with 2) because the latch rarely arms: leak severity determines transcription quality, so a leak quiet enough to be garbled is garbled consistently, while verbatim echo comes from a louder leak. The regimes are near-disjoint rather than sequential. Kept anyway because it changes which error you get — unconditional, a working AEC drops real speech; latched, a leaking AEC produces ghost turns. Timing is the actual fix. Also here: - suppress short commits with no Silero speech since the last commit, which is how ElevenLabs' "Yes."/"Yeah." on trailing silence became turns (6 of 9 EL failures) - baseline refusal now triggers only when a scenario fails every repeat, so a probabilistic axis can gate at all; at --repeat 2 five leak scenarios looked broken and three were intermittent at 4 - first baseline for deepgram-flux/local[leak=0.15] --- benchmarks/voice/README.md | 87 +++++++++++--- benchmarks/voice/baseline.json | 77 ++++++++++++ benchmarks/voice/cli.py | 20 +++- benchmarks/voice/scenario.py | 27 ++++- python/tests/voice/test_deepgram.py | 2 +- python/tests/voice/test_namo.py | 2 +- python/tests/voice/test_turn_detection.py | 135 ++++++++++++++++----- python/timbal/voice/session.py | 32 +++++ python/timbal/voice/turn_detection.py | 136 ++++++++++++++++++++-- 9 files changed, 459 insertions(+), 59 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 444b939b..1f361988 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -97,6 +97,9 @@ speech makes the assistant uninterruptible, the worse of the two failures. | leak 0.15, ghost turns | 12 per 78 runs | **6** | | clean, 4 baselined cells | 100% | **100%, no regressions** (126 runs) | +Those numbers stood for a few hours. The clean-run check below missed the case that +undoes them — see "the suppressor ate a real turn on a clean run". + The clean-run check is the one that matters for shipping it: a suppressor that catches more echo can start eating genuine interruptions. All seven baselined cells were run, and the decisive one is `deepgram-flux/provider`, where `_likely_stt_echo` is the *only* @@ -159,20 +162,76 @@ other. Neither test suite could catch it because each mechanism is right in isol | \+ grace window | 6 | 0/3 | | \+ rescue guard | **2** | **3/3** | -Eleven of the thirteen leak markers were retired by this. The two that remain are -different in kind: `support_barge_in_one_word` gets the echo tail and the user's word in -a *single* commit (`'retailers. Stop.'`), so suppressing it loses the barge-in the -scenario tests — that needs the echo span located inside the commit, not a verdict on -the whole string. - -**The axis still will not baseline, and the refusal is the finding.** At `--repeat 3` it -scores 94% with all six failures flaky — `banking_digits_pause`, `coding_barge_in`, -`food_simple`, `medical_barge_in_twice`, each passing some repeats — plus three session -timeouts. Which scenarios trip depends on how the STT happens to garble a given reply, -so successive runs surface different members and a marker set fitted to one run is -fitted to noise. Two samples of the suite are not enough to tell a 90%-reliable scenario -from a broken one; that needs repeats in the tens, which is the next real step here -rather than more marker churn. +Eleven of the thirteen leak markers were retired by this. One of the two that remained is +different in kind and survives everything below: `support_barge_in_one_word` gets the echo +tail and the user's word in a *single* commit (`'retailers. Stop.'`), so suppressing it +loses the barge-in the scenario tests — that needs the echo span located inside the commit, +not a verdict on the whole string. + +**Then the suppressor ate a real turn on a clean run, which reframes everything above.** +`food_long_pause` on `elevenlabs/lexical` went 4/4 → 0/4. The user says "Pepperoni pizza, +please." after a reply of "Got it — a large pepperoni pizza.", and the check drops it — +on a run with no leak injected at all, suppressing echo that could not exist. It scores +0.67, inside the 0.68–1.00 band the threshold was calibrated on. + +The calibration was not wrong about its samples; it was drawn only from barge-ins, where +the user is *changing* the subject and shares little vocabulary with the reply. But +confirmations, disambiguation and digit readback all put the user's next words into the +reply by design, and there the populations interleave — genuine speech at 0.67 and 0.78 +against real echo at 0.76 and 0.79. No threshold splits that, so this is not a tuning +problem, and a per-utterance "is this echo?" has no reliable text-only answer. + +**So resemblance was latched behind proof.** The check is now two branches with different +standing: a verbatim substring of what is playing is evidence and always counts, while +garbled resemblance is a guess, armed only once the same session has produced verbatim +echo. The argument was that base rate decides it — when AEC works there is no echo in the +signal at all, so every fuzzy suppression is a false positive by construction, and when it +leaks the verbatim branch will see it. + +**It never arms, and the reason invalidates the design rather than its tuning.** Every +remaining ghost under leak is garbled and not one is verbatim: `'surprised retailers.'`, +`'Veroni, anything else?'`, `'Nash exactly once.'`, `'Not anything else?'`. Leak severity +determines transcription quality. A leak quiet enough to be garbled is garbled +*consistently* — the STT is transcribing faint, distorted audio, so of course every copy +comes back wrong — while verbatim echo belongs to a louder, cleaner leak. The two are +near-disjoint regimes rather than sequential stages, so "verbatim echo seen" does not +predict "garbled echo present", and a 20-second scenario never earns its proof. + +| leak 0.15, deepgram-flux/local | gated pass | ghost turns | +| --- | --- | --- | +| unconditional resemblance | ~100% (13 markers) | 2 | +| latched behind proof | 85% (2 markers) | 10 | + +**Kept regardless, because it changes which error you get.** Unconditional, a *working* +AEC drops genuine user speech and the assistant answers something the user never said. +Latched, a *leaking* AEC produces ghost turns. A ghost turn on a broken microphone is +plainly the lesser harm, so the latch dominates on worst case even though it gives the +leak numbers back. The real fix is timing, which is the only signal that survives both +regimes: echo of a word arrives while that word is playing, and a user repeating it does +so afterwards. Text similarity cannot see that and never will. + +One narrowing worth recording, since the earlier entry over-claimed: the latch restored +`food_long_pause` on `elevenlabs/lexical` only. It still fails on `deepgram-flux/provider` +and `deepgram-nova/lexical`, so those are a different cause and folding them into the echo +story was wrong. + +**The axis baselines now, and the old refusal rule was what blocked it.** At `--repeat 4` +it scores 85% with per-scenario rates recorded, and only `banking_digits` and +`banking_digits_pause` fail every repeat. The previous rule — refuse if anything fails — +demanded that a probabilistic axis be perfect before it could gate at all, so the axis +never gated and its markers were fitted to whichever run was in front of me. Refusal now +triggers only on a scenario that fails *every* repeat; flaky ones are recorded at their +measured rate. The repeat count matters more than expected: at `--repeat 2` five scenarios +looked hard and three of those five turned out to be intermittent at 4. + +Digit readback is the honest residual, and it is the worst case from both directions at +once. Digits never produce verbatim echo — a run of digits garbles into other digits — so +the filter never arms. And the obvious repair, trusting resemblance here because a readback +plainly echoes, is exactly backwards: the reply *is* the user's digits, so a genuine +correction ("Four four eight." against "…account four four seven.") scores 0.75. It is +where resemblance is least informative and most tempting. + +Still open on this axis: 4 session errors per 120 runs under leak, untriaged. Both mechanisms that consume mic energy were ruled out as causes by disabling them: the hold's VAD extension (`HOLD_VAD_MAX_EXTENSION_SECS = 0`) and the stale-partial diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index 81614289..4f073aea 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -129,6 +129,83 @@ "wall_secs": 838.0, "jobs": 6 }, + "deepgram-flux/local[leak=0.15]": { + "label": "deepgram-flux/local[leak=0.15]", + "stt": "deepgram-flux", + "detector": "local", + "runs": 120, + "passed": 102, + "pass_rate": 0.85, + "ghost_turns": 10, + "errors": 4, + "latency_p50": 228.4, + "latency_p95": 314.9, + "latency_min": 169.6, + "latency_max": 440.3, + "latency_samples": 207, + "dead_air_p50": 728.2, + "dead_air_p95": 1974.2, + "dead_air_samples": 195, + "per_scenario": { + "banking_hesitation": 1.0, + "banking_short_reject": 0.75, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 0.5, + "coding_followup_after_reply": 0.75, + "coding_pause": 1.0, + "coding_simple": 0.75, + "food_barge_in": 0.75, + "food_list_pause": 1.0, + "food_long_pause": 1.0, + "food_pause": 0.5, + "food_rapid_fire": 1.0, + "food_simple": 0.25, + "food_trailing_preposition": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 0.25, + "medical_filler_midway": 1.0, + "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 0.5, + "support_closer": 1.0, + "support_echo_silence": 0.75, + "support_pause": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 0.75, + "support_trailing_conjunction": 1.0 + }, + "flaky": [ + "banking_short_reject", + "coding_barge_in_echo", + "coding_followup_after_reply", + "coding_simple", + "food_barge_in", + "food_pause", + "food_simple", + "medical_barge_in_twice", + "support_barge_in_late", + "support_echo_silence", + "support_simple" + ], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "banking_digits", + "banking_digits_pause", + "coding_double_pause", + "food_backchannel", + "medical_hesitant_pause", + "medical_self_correction", + "support_barge_in_one_word" + ], + "unexpected_passes": [], + "wall_secs": 1212.7, + "jobs": 6 + }, "deepgram-flux/provider": { "label": "deepgram-flux/provider", "stt": "deepgram-flux", diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index 4cbb2962..be93beae 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -299,15 +299,27 @@ def log(kind: str, detail: str = "") -> None: print(f" known: {name} — {reason}") if args.update_baseline: - if card.pass_rate < 1.0: - # Saving here would record the failure as the accepted status quo - # and disarm its gate. Either fix it, or mark it known_failure. + # Only a scenario that failed *every* repeat blocks. Saving one would + # record broken behavior as the accepted status quo and disarm its gate, + # which is what this guard is for — but it used to refuse on any failing + # run at all, and that is how a stale baseline outlives the truth. The + # ElevenLabs cells kept asserting a pass rate of 1.0 taken before a + # regression, gating every later run against a number only luck could + # meet, because one flaky repeat in forty was enough to block the + # refresh. A partial rate is not a broken baseline: `per_scenario` + # records 0.75 and the gate fires when it drops, which is strictly more + # honest than an unreachable 1.0 or a `known_failure` marker claiming a + # scenario cannot pass when it passes three times in four. + hard = sorted(name for name, rate in card.per_scenario.items() if rate == 0.0) + if hard: print( "\n refusing to update the baseline: " - f"{card.runs - card.passed} run(s) failed and are not marked known_failure" + f"{', '.join(hard)} failed every repeat and are not marked known_failure" ) exit_code = 1 continue + if card.flaky: + print(f"\n recording flaky scenarios at their measured rate: {', '.join(card.flaky)}") save_baseline(card) print(f" baseline updated for {card.label}") continue diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 8789fb0d..4d7004c3 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -595,6 +595,27 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ) _ECHO_LEAK_CELL = "deepgram-flux/local" +# Digit readback is the worst case for echo, from both directions at once. +# +# Garbled echo is only suppressed once a session has proved it leaks, by producing one +# verbatim echo first (`TurnDetector.echo_verdict`). Digits never get there: the leak +# is quiet, so the STT garbles every copy of it, and a run of digits garbles into other +# digits that still resemble the reply. Nothing verbatim ever arrives to arm the filter. +# +# And the obvious repair — trust resemblance here, since a readback obviously echoes — +# is exactly backwards. The reply *is* the user's digits, so a genuine correction +# ("Four four eight." against "…account four four seven.") scores 0.75, inside the range +# real echo occupies. Digit readback is where resemblance is least informative and most +# tempting, which is why these two are marked rather than tuned around. +# +# Both are gated on measurement, not marked: everything else that fails under leak is +# intermittent and the baseline now records it at its true rate. Only these two fail +# every repeat. +_ECHO_GARBLED_DIGITS = ( + "garbled echo of a digit readback: the session never produces verbatim echo to arm " + "the resemblance check, and resemblance cannot be trusted when the reply is the digits" +) + _PROVIDER_ENDPOINTING_FAILURE = ( "`provider` defers to Flux's endpointing, which splits here; `lexical` merges it " "correctly because Namo scores the fragment 0.00 incomplete" @@ -816,8 +837,8 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "is letting echo through rather than over-suppressing.\n\n" "0.15 was recorded as clean here and is not: it fails ~1 in 3. The original reading " "came from too few repeats on the one scenario the leak axis was ever run against. " - "Running the whole suite at 0.15 fails nine scenarios, which is why the marker now " - "lives on all of them rather than here alone.\n\n" + "The axis now carries its own baseline, so the whole suite's leak behaviour is " + "recorded at measured rates instead of being marked scenario by scenario.\n\n" "The mechanism is visible in what gets committed: 'Our retailers.', 'Arise " "retailers.', 'has aroused retailers.' — all manglings of the reply's own tail, " "'...authorized retailers.' The suppressor is a text-similarity check against " @@ -1170,6 +1191,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: # look like a hallucinated turn to every text comparison. script=[Say("My account number is four four seven two nine one."), *_SETTLE], expect=[UserTurns(1), NoGhostTurns(), Interrupted(False), NoErrors()], + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_GARBLED_DIGITS}, note="Digit strings are the STT-hostile case: no lexical context to fall back on.", ), Scenario( @@ -1191,6 +1213,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", }, + known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_GARBLED_DIGITS}, intermittent=True, note=( "The hardest merge in the suite: a digit string broken across a pause, with no " diff --git a/python/tests/voice/test_deepgram.py b/python/tests/voice/test_deepgram.py index 2409709e..3e67ab55 100644 --- a/python/tests/voice/test_deepgram.py +++ b/python/tests/voice/test_deepgram.py @@ -12,11 +12,11 @@ import pytest from timbal.voice.deepgram import ( + _AUDIO_FLUSH_BYTES, DEFAULT_FLUX_MODEL, DEFAULT_NOVA_MODEL, DeepgramFluxSTT, DeepgramNovaSTT, - _AUDIO_FLUSH_BYTES, effective_stt_model, is_flux_model, resolve_stt, diff --git a/python/tests/voice/test_namo.py b/python/tests/voice/test_namo.py index cfa95094..65da251f 100644 --- a/python/tests/voice/test_namo.py +++ b/python/tests/voice/test_namo.py @@ -16,10 +16,10 @@ from timbal.voice import turn_detection as turn_detection_module # noqa: E402 from timbal.voice.eou import PunctuationEouPredictor # noqa: E402 from timbal.voice.namo import ( # noqa: E402 + _ACK_FORCE_P, DEFAULT_REPO_ID, MULTILINGUAL_REPO_ID, NamoTextEouPredictor, - _ACK_FORCE_P, _prepare_text_for_namo, ) diff --git a/python/tests/voice/test_turn_detection.py b/python/tests/voice/test_turn_detection.py index 3e8129cd..76a82c65 100644 --- a/python/tests/voice/test_turn_detection.py +++ b/python/tests/voice/test_turn_detection.py @@ -10,6 +10,7 @@ from contextlib import aclosing +import pytest from timbal import Agent from timbal.core.test_model import TestModel from timbal.voice.eou import AudioEouModel, PunctuationEouPredictor, TextEouPredictor @@ -28,6 +29,7 @@ TurnState, _is_garbage_commit, _is_same_user_utterance_refinement, + _is_unvoiced_hallucination, _likely_stt_echo, resolve_turn_detector, ) @@ -35,11 +37,56 @@ from .test_session import MockSTT, MockTTS +class TestUnvoicedHallucination: + """A silent mic may veto ElevenLabs' inventions, and nothing else. + + The filter runs without the ``_vad_evidence`` gate, so what stops it suppressing + real speech is only its narrowness. These pin that: the phrases are the ones + actually observed committed on trailing silence, and the negatives are the short + barge-ins nearby in length that must survive. + """ + + @staticmethod + def _state(*, mic_speech: bool | None) -> TurnState: + return TurnState( + assistant_active=False, + audio_playing=False, + assistant_text="", + active_user_text="", + seconds_since_turn_start=1.0, + seconds_since_last_commit=1.4, + partials_since_last_commit=2, + mic_speech_since_last_commit=mic_speech, + ) + + @pytest.mark.parametrize("text", ["Yes.", "Yeah.", "Okay.", "Bye.", "I don't."]) + def test_silent_mic_vetoes_stock_phrases(self, text: str) -> None: + assert _is_unvoiced_hallucination(text, self._state(mic_speech=False)) + + @pytest.mark.parametrize("text", ["Stop.", "Yes.", "Wait, hold on.", "Actually, cancel that."]) + def test_mic_energy_admits_everything(self, text: str) -> None: + """A real interruption carries energy, which is what makes the filter safe: + even a one-word "Stop." is untouchable once Silero has heard it.""" + assert not _is_unvoiced_hallucination(text, self._state(mic_speech=True)) + + @pytest.mark.parametrize("text", ["Wait, hold on.", "Actually, cancel that.", "No, the white one."]) + def test_longer_barge_ins_survive_a_silent_mic(self, text: str) -> None: + """The second belt: over two words, VAD alone cannot drop it. Silero misses + quiet speech, and losing a real instruction costs more than a ghost turn.""" + assert not _is_unvoiced_hallucination(text, self._state(mic_speech=False)) + + def test_no_opinion_never_suppresses(self) -> None: + """``None`` is no endpointer or too long a gap to judge — distinct from False, + and reading it as False would drop turns on every session without Silero.""" + assert not _is_unvoiced_hallucination("Yeah.", self._state(mic_speech=None)) + + class TestLikelySttEcho: - """Garbled echo must be suppressed; genuine speech against the same reply must not. + """Garbled echo must be suppressed, but only in a session shown to leak. - Both lists are real transcripts from ``--aec-leak`` runs, so this pins the margin - the threshold was calibrated on rather than restating the implementation. + The transcripts are real, from ``--aec-leak`` runs. What they pin is the split + between the two branches: verbatim echo is evidence and always counts, garbled + echo is a guess that stays disarmed until the verbatim branch has fired. """ REPLY = ( @@ -48,38 +95,70 @@ class TestLikelySttEcho: "of purchase from one of our authorized retailers." ) SEGFAULT_REPLY = "A segfault means bad memory access." + GARBLED = ( + "Our retailers.", + "Arise retailers.", + "Advised retailers.", + "advertised retailers.", + "Archives to retailers.", + "has aroused retailers.", + ) + + @staticmethod + def _state(reply: str) -> TurnState: + return TurnState( + assistant_active=True, + audio_playing=True, + assistant_text=reply, + active_user_text="", + seconds_since_turn_start=2.0, + seconds_since_last_commit=2.0, + partials_since_last_commit=1, + ) - def test_garbled_echo_is_suppressed(self) -> None: - """The old check scored these 0.23-0.33 against a 0.68 threshold and passed - every one through: it compared the commit to a tail sized at 3x its length, - which caps ratio() at 0.50, so the branch could never fire.""" - for echo in ( - "Our retailers.", - "Arise retailers.", - "Advised retailers.", - "advertised retailers.", - "Archives to retailers.", - "has aroused retailers.", - ): - assert _likely_stt_echo(echo, self.REPLY), echo - - def test_genuine_barge_ins_survive(self) -> None: + def test_garbled_echo_needs_a_leaking_session(self) -> None: + """Unlatched, none of these may be suppressed: the same scores are produced by + a user repeating the assistant, and dropping their turn is the worse error.""" + detector = HeuristicTurnDetector() + for echo in self.GARBLED: + assert not detector.echo_verdict(echo, self._state(self.REPLY)), echo + + def test_verbatim_echo_arms_the_garbled_branch(self) -> None: + """One verbatim leak is proof the mic hears the speaker, and from then on + resemblance is admissible. This is the whole mechanism in three lines.""" + detector = HeuristicTurnDetector() + state = self._state(self.REPLY) + assert detector.echo_verdict("authorized retailers.", state) + for echo in self.GARBLED: + assert detector.echo_verdict(echo, state), echo + + def test_the_latch_does_not_leak_across_sessions(self) -> None: + """Detectors are cloned per session, so proof from one call must not arm another.""" + leaking = HeuristicTurnDetector() + assert leaking.echo_verdict("authorized retailers.", self._state(self.REPLY)) + assert not HeuristicTurnDetector().echo_verdict("Our retailers.", self._state(self.REPLY)) + + def test_genuine_barge_ins_survive_even_when_latched(self) -> None: + detector = HeuristicTurnDetector() + state = self._state(self.REPLY) + detector.echo_verdict("authorized retailers.", state) for real in ("Actually, cancel that.", "Wait, hold on.", "Okay, never mind.", "Okay, thanks."): - assert not _likely_stt_echo(real, self.REPLY), real + assert not detector.echo_verdict(real, state), real - def test_user_quoting_the_assistant_survives(self) -> None: - """The tightest case in the suite (`coding_barge_in_echo`): the user repeats the - assistant's own words, which is what asking someone to clarify sounds like. It - scores 0.58 against echo's 0.68 floor — the whole margin, so it guards it.""" - reply = "Python caches imported modules, so the module body runs exactly once." - assert not _likely_stt_echo("Sorry, the module cache?", reply) - assert _likely_stt_echo("When look exactly once.", reply) + def test_assistant_repeating_the_user_is_not_echo(self) -> None: + """The regression that produced the latch. `food_long_pause` lost the user's + order to a confirmation containing it, on a clean run where no echo existed — + and it scores 0.67, inside the range real echo occupies, so only the absence + of proof can save it.""" + reply = "Got it — a large pepperoni pizza." + assert not HeuristicTurnDetector().echo_verdict("Pepperoni pizza, please.", self._state(reply)) - def test_exact_substring_still_suppressed(self) -> None: + def test_verbatim_branch_is_exact_only(self) -> None: assert _likely_stt_echo("memory access.", self.SEGFAULT_REPLY) + assert not _likely_stt_echo("and memory access.", self.SEGFAULT_REPLY) def test_no_assistant_text_is_never_echo(self) -> None: - assert not _likely_stt_echo("Our retailers.", "") + assert not HeuristicTurnDetector().echo_verdict("Our retailers.", self._state("")) # --------------------------------------------------------------------------- diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index 12d2a542..2d289797 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -976,6 +976,34 @@ def _vad_hears_speech_now(self, since_monotonic: float) -> bool: # hostage for as long as the session lives. MAX_QUIET_SPEECH_SECS = 0.1 + # Never look further back than the endpointer keeps speech history for, or a + # window longer than the buffer would read as silence and convict a real turn. + MAX_HALLUCINATION_LOOKBACK_SECS = 3.0 + + def _mic_speech_since_last_commit(self) -> bool | None: + """Whether Silero heard the user speak since the previous commit. + + ``None`` means no opinion, and the caller must not suppress on it: no + endpointer, no commit to measure from, or a gap longer than the speech + history, where "no speech in the buffer" says nothing about the utterance + that produced this commit. + + Anchored on the last commit rather than a trailing window because a fixed + window cannot work here. ElevenLabs commits roughly 1.6s after the audio, so + any window wide enough not to convict a real late commit is also wide enough + to still contain the *previous* utterance and acquit an invented one. The gap + since the last commit is the interval the new text must account for. + """ + if self._endpointer is None or not self._last_commit_at: + return None + window = time.monotonic() - self._last_commit_at + if window <= 0 or window > self.MAX_HALLUCINATION_LOOKBACK_SECS: + return None + speech_secs = self._endpointer.speech_secs_in_window(window) + if speech_secs is None: + return None + return speech_secs >= self.MIN_BARGE_IN_VAD_SPEECH_SECS + # Trailing window Silero must find quiet before a partial can be called invented. # Shorter than the barge-in window because this fires between utterances, where # the pause is the signal, not during one. @@ -1096,6 +1124,9 @@ async def _sweep_stale_partials(self) -> None: # This rescue exists for user speech an over-eager AEC ducked # below the provider's commit threshold, which is the one thing # echo is not. + # Verbatim only, deliberately: this runs outside the detector and so + # outside its leak latch, and rescuing is the last chance a stranded + # utterance gets. The traced case was an exact substring anyway. if _likely_stt_echo(self._latest_partial_text, self._turn_assistant_text): logger.debug("stt_stale_partial_echo_skipped", text_preview=self._latest_partial_text[:80]) continue @@ -1203,6 +1234,7 @@ def _turn_state(self) -> TurnState: seconds_since_assistant_active=( None if assistant_active or not self._last_assistant_active_at else now - self._last_assistant_active_at ), + mic_speech_since_last_commit=self._mic_speech_since_last_commit(), partials_since_last_commit=self._partials_since_last_commit, holding=holding, ) diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index 09a230da..71ef0f55 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -70,6 +70,12 @@ class TurnState(BaseModel): """User text of the in-flight turn, or the pending HOLD fragment when holding.""" seconds_since_turn_start: float seconds_since_last_commit: float + mic_speech_since_last_commit: bool | None = None + """Whether local VAD heard the user speak since the previous commit. + + ``None`` is "no opinion" — no VAD, or too long a gap to judge — and must never + be read as ``False``. + """ seconds_since_assistant_active: float | None = None """Seconds since the assistant was last speaking, or ``None`` while it still is. @@ -126,6 +132,43 @@ async def close(self) -> None: # noqa: B027 def push_audio(self, chunk: bytes) -> None: # noqa: B027 """Raw mic PCM, for detectors that run local VAD / audio models.""" + _echo_leak_seen: bool = False + """This session has produced verbatim echo, so its AEC demonstrably leaks.""" + + def echo_verdict(self, text: str, state: TurnState) -> bool: + """Whether ``text`` is the assistant hearing itself. + + Two branches with very different standing. A verbatim substring of what is + playing is direct evidence and always counts. Garbled resemblance is a guess, + and only allowed once this session has produced verbatim echo at least once. + + The gate exists because the base rate is everything here. When AEC works — a + browser, a headset, most calls — there is no echo in the signal at all, so + *every* fuzzy suppression is a false positive by construction, and the cost is + the user's turn being silently dropped. When AEC leaks, echo is not a one-off + but a property of the session, and the verbatim branch will see it. So rather + than asking the unanswerable per-utterance question, ask the easy per-session + one first and let the answer arm the aggressive filter. + + Found the hard way. With the fuzzy branch unconditional, `food_long_pause` + lost the user's "pepperoni pizza please." to a reply of "Got it — a large + pepperoni pizza." on a *clean* run with no leak injected at all — the + suppressor firing on echo that could not exist. + + The residual risk is the mirror image: a microphone that leaks only + distorted, never verbatim, never arms the fuzzy branch and keeps its ghost + turns. That is the better failure to have, and worth stating plainly because + the leak corpus behind these thresholds is synthetic — ``--aec-leak`` mixes a + scaled copy of the TTS into the mic, which yields cleaner substrings than a + real speaker in a real room, and so flatters this design. + """ + if not _echo_window_open(state): + return False + if _likely_stt_echo(text, state.assistant_text): + self._echo_leak_seen = True + return True + return self._echo_leak_seen and _resembles_stt_echo(text, state.assistant_text) + def clone(self) -> TurnDetector: """Per-session copy for shared configs (server ``voice_config``). @@ -250,6 +293,41 @@ def _normalize_echo(s: str) -> str: _ECHO_WINDOW_RATIO = 0.65 +# Longest commit a silent mic is allowed to veto. ElevenLabs' inventions on trailing +# silence are one- and two-word stock phrases — "Yes.", "Yeah.", "Okay." — while the +# short barge-ins worth protecting run longer ("Wait, hold on.", "Actually, cancel +# that.") and carry mic energy regardless. Two words leaves margin on both sides. +MAX_UNVOICED_COMMIT_WORDS = 2 + + +def _is_unvoiced_hallucination(text: str, state: TurnState) -> bool: + """A short commit the local VAD can prove the user never spoke. + + ElevenLabs invents stock phrases on trailing silence and *commits* them, not + merely emits them as partials, so they arrive as turns of their own: measured + across `coding_barge_in_echo`, `food_simple`, `medical_barge_in`, + `medical_barge_in_twice`, `support_barge_in` and `support_pause_short`, this one + behaviour accounts for six of the nine residual failures on the two ElevenLabs + cells and every ghost turn among them. + + Unlike the neighbouring VAD gates this does not require + :attr:`~timbal.voice.VoiceSession._vad_evidence`, and the exception is deliberate. + That flag exists to stop inference behaviours switching on for detectors that + never had them, above all ones that could render the assistant uninterruptible — + but a real interruption carries mic energy by definition, so the only thing this + can suppress is a two-word commit for which Silero heard nothing at all in the + gap since the previous one. Half the failures it addresses are on ``lexical``, + which has no audio EOU and would therefore never see the fix. + + Silero's own failure mode is missing *quiet* speech, which is why the caller + abandons the judgement when the gap since the last commit outruns the speech + history rather than guessing from an empty buffer. + """ + if state.mic_speech_since_last_commit is not False: + return False + return len(text.split()) <= MAX_UNVOICED_COMMIT_WORDS + + # How long after the assistant stops speaking its echo may still arrive. # # STT commits lag the audio that produced them — ~0.3s of endpointing on Deepgram @@ -280,18 +358,40 @@ def _echo_window_open(state: TurnState) -> bool: def _likely_stt_echo(committed: str, assistant_so_far: str) -> bool: - """True if STT text is probably the assistant's own speech leaking into the mic.""" + """The assistant's own words came back, verbatim. + + Kept exact on purpose. A verbatim substring of what is playing right now is the + only echo evidence that cannot also be produced by a user saying the same thing, + which makes this the branch safe to run unconditionally — and the branch worth + latching the fuzzy one behind. + """ c = _normalize_echo(committed) a = _normalize_echo(assistant_so_far) if not a: return False # Short leaks (punctuation / tail of TTS) often transcribe as 1–9 chars. if len(c) < 10: - if len(c) >= 2 and c in a: - return True + return len(c) >= 2 and c in a + return c in a + + +def _resembles_stt_echo(committed: str, assistant_so_far: str) -> bool: + """The assistant's words came back *garbled* — a judgement, not an observation. + + Only meaningful once something else has established that this microphone leaks; + see :meth:`TurnDetector.echo_verdict`. On its own it cannot be trusted, because + text similarity cannot separate echo from a user repeating the assistant, and + that is not a corner case — confirmations, disambiguation and digit readback all + put the user's next words into the reply by design. Measured against real + transcripts the two populations interleave: genuine speech scores 0.67 for + "Pepperoni pizza, please." against "Got it — a large pepperoni pizza." and 0.78 + for "Yes, the blue one.", while true echo scores 0.76 and 0.79 for + "advertised retailers." and "Our retailers.". No threshold splits that. + """ + c = _normalize_echo(committed) + a = _normalize_echo(assistant_so_far) + if not a or len(c) < 10: return False - if c in a: - return True tail_len = min(len(a), max(len(c) * 3, 100)) tail = a[-tail_len:] if len(tail) <= len(c): @@ -421,7 +521,7 @@ async def on_partial(self, text: str, state: TurnState) -> PartialDecision: return PartialDecision.IGNORE is_noise = _is_noise(text) is_hesitation = _is_hesitation_only(text) - is_echo = _likely_stt_echo(text, state.assistant_text) if not is_noise else False + is_echo = self.echo_verdict(text, state) if not is_noise else False too_short = len(text) < self.MIN_BARGE_IN_PARTIAL_CHARS or len(text.split()) < self.MIN_BARGE_IN_PARTIAL_WORDS if not is_noise and not is_hesitation and not is_echo and not too_short: return PartialDecision.BARGE_IN @@ -456,8 +556,10 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: and not state.holding ): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination") - if _echo_window_open(state) and _likely_stt_echo(text, state.assistant_text): + if self.echo_verdict(text, state): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") + if _is_unvoiced_hallucination(text, state): + return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination_no_vad") # Pending HOLD: STT often re-commits a longer form of the same fragment. # Mid-turn "refinement" IGNORE would freeze the held text until timeout — # re-HOLD with the updated utterance instead (session trusts decision.text). @@ -582,7 +684,7 @@ async def on_partial(self, text: str, state: TurnState) -> PartialDecision: return PartialDecision.IGNORE if _is_noise(text) or _is_garbage_commit(text) or _is_hesitation_only(text): return PartialDecision.IGNORE - if _likely_stt_echo(text, state.assistant_text): + if self.echo_verdict(text, state): return PartialDecision.IGNORE # Same min-words gate as HeuristicTurnDetector: one short partial while # the assistant is speaking is more often a mic blip than a barge-in. @@ -597,8 +699,10 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: return CommitDecision(action=CommitAction.IGNORE, text=text, reason="garbage") if _is_hesitation_only(text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hesitation") - if _echo_window_open(state) and _likely_stt_echo(text, state.assistant_text): + if self.echo_verdict(text, state): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") + if _is_unvoiced_hallucination(text, state): + return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination_no_vad") return CommitDecision(action=CommitAction.NEW_TURN, text=text, reason="provider") @@ -751,6 +855,20 @@ class LocalAudioTurnDetector(HeuristicTurnDetector): # # 3.0 scores higher still on pause merges (90% vs 81%) and is not worth it: # p95 dead air goes to 3617ms and `support_pause_short` starts failing. + # + # Re-measured once the replay harness was found to tear down mid-hold — its + # quiescence window was shorter than this timeout, so any hold that outlived it + # scored as the product losing a turn, which biased every number above toward + # shorter holds. The conclusion survives the correction, but 2.0 deserved the + # look: at 52 runs a value it read as a free win (88% against 83% for 16ms at + # the median) and did not replicate at 156 — 85% against 82%, four runs inside + # one standard deviation, while p95 dead air went 1791 -> 3204ms. + # + # What the per-scenario split suggests is that no single value is right, since + # five scenarios improve and five regress: `banking_digits_pause` wants 2.0 + # (67% -> 100%), `support_pause_short` wants 1.2 (100% -> 83%). A tier keyed on + # something other than text completeness is the interesting direction, not + # another sweep of this constant. TEXT_COMPLETE_HOLD_TIMEOUT_SECS = 1.2 # The tier needs *confidently* finished text (terminal punctuation scores # P_TERMINAL=0.95), not the predictor's complete-leaning neutral (0.60) — From 21dc3f9bf6e5b79cd827d4f211116d6843becce9 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 13:07:59 +0200 Subject: [PATCH 18/30] fix(voice): only a commit may prove the mic leaks; baseline all 12 cells MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The echo latch armed itself on clean runs and cost real turns. `food_long_pause` went 100% -> 0% on deepgram-flux/provider and deepgram-nova/lexical, with 'pepperoni pizza, please.' suppressed as echo while no leak was injected — which only the resemblance branch can do, so proof had arrived from somewhere. It came from the user's own partials: the STT emits `Pepperoni`, then `Pepperoni pizza`, and that is a verbatim substring of "Got it — a large pepperoni pizza." So the assumption in the previous commit was wrong. A verbatim substring *can* be produced by a user saying the same thing, and confirmation flows are where it happens, because the reply restates the request. Length does not separate them either: the echo this catches is 'memory access' at 13 chars, the false proof is 'pepperoni pizza' at 15. What separates them is the kind of event. A partial is text the STT is still revising; a commit is a claim it has settled Only commits arm the latch now. Suppressing an echo-shaped partial is unchanged and was never the problem. food_long_pause returns to 100% on both cells, and banking_correction and support_barge_in clear with it. Then the full matrix, 12 cells x 39 scenarios x 3 repeats: - zero ghost turns in 1386 runs, where they were routine this morning - all 12 cells baselined, up from 7 — and 2 of those 7 held pass=1.0 entries predating today, so they would have passed a gate they should have failed - the hold path priced for the first time: holdless detectors score 65-69% on Nova and ElevenLabs against 98-100% with a hold, failing one family (pause merging), marked per cell with _NO_HOLD_TO_MERGE Per cell rather than per detector because deepgram-flux/heuristic scores 90% on that same holdless detector — Flux holds the fragment provider-side — so a blanket rule would mark nine scenarios it passes and hide regressions in them. --- benchmarks/voice/README.md | 62 +++ benchmarks/voice/baseline.json | 525 ++++++++++++++++++---- benchmarks/voice/scenario.py | 73 ++- python/tests/voice/test_turn_detection.py | 15 +- python/timbal/voice/turn_detection.py | 18 +- 5 files changed, 590 insertions(+), 103 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 1f361988..cb708f01 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -233,6 +233,68 @@ where resemblance is least informative and most tempting. Still open on this axis: 4 session errors per 120 runs under leak, untriaged. +**The latch then armed itself on a clean run, and the mechanism refutes the claim above.** +`food_long_pause` went 100% → 0% on `deepgram-flux/provider` and `deepgram-nova/lexical`, +and the trace shows `'pepperoni pizza, please.'` suppressed as echo while the reply is +still playing — which only the *resemblance* branch can do, so the latch was armed on a +run with no leak. What armed it was the user's own partials. The STT emits `Pepperoni`, +then `Pepperoni pizza`, and `'pepperoni pizza'` is a verbatim substring of "Got it — a +large pepperoni pizza." + +So "a verbatim substring cannot also be produced by a user saying the same thing" is +false, and confirmation flows are exactly where it is false: the reply restates the +request, so the user's words are a substring of it by construction. Length does not +separate the cases either — the echo this exists to catch is `'memory access'` at 13 +characters and the false proof is `'pepperoni pizza'` at 15. + +What does separate them is *what kind of event* the evidence is. A partial is text the STT +is still revising, and reading it as evidence about the microphone is a category error; +a commit is a claim the provider has settled on. Only commits arm the latch now. +Suppressing an echo-shaped partial still happens and predates all of this — that was never +the problem, arming on it was. `food_long_pause` returns to 100% on both cells, and +`banking_correction` and `support_barge_in`, which regressed the same way, clear with it. + +**Full matrix, 12 cells × 39 scenarios × 3 repeats: zero ghost turns.** Not one in 1386 +runs, against a suite where they were routine this morning. That is the clearest signal +that the day's filters — resemblance latched to commits, the unvoiced-commit guard, the +watchdog's echo check — are subtracting spurious turns without eating real ones. + +It also prices the hold path for the first time, because five cells had never been +baselined and four of them are holdless. Raw rates, before the pause family was marked +on those cells — they read 100% now, which is the point of marking, so these numbers +only exist here: + +| detector | ElevenLabs | Flux | Nova | +|---|---|---|---| +| `heuristic` (no hold) | 69% | **90%** | 67% | +| `provider` (no hold) | 68% | 96% | 65% | +| `lexical` | 98% | 100% | 96% | +| `local` | 100% | 100% | 99% | + +The holdless cells fail one family — pause merging — and fail it identically: `nova/heuristic` +and `nova/provider` miss the same 12 scenarios, both ElevenLabs cells the same 11. With no +hold, every fragment the STT commits is a turn boundary and nothing downstream can merge +it, so roughly 30 points of the suite is what holding buys. + +`deepgram-flux/heuristic` at 90% is the exception that makes it an STT × detector fact +rather than a detector one: Flux holds the fragment provider-side before any detector sees +it, so the same holdless detector merges nine of the scenarios Nova's cannot. That is why +the markers are written per cell — a blanket "holdless cannot merge" rule would mark those +nine as expected failures on Flux and hide any future regression in them. + +**All twelve cells now gate.** Previously seven did, and two of those seven compared against +`pass=1.0` entries recorded before the day's changes, so they would have passed a gate they +should have failed. What is left is flaky rather than broken and recorded at measured rates: +`coding_double_pause` on three cells, `medical_barge_in` and `banking_digits_pause` on +`elevenlabs/lexical`, `food_long_pause` and `coding_pause` on `deepgram-nova/local`. One +ghost turn survives, on `deepgram-flux/provider` in `medical_simple` — the only one in the +matrix, and untriaged. + +Two things this run does *not* establish, worth stating so the baseline is not over-read. +Latency and dead air were measured at `--jobs 6`, so they gate only against future runs at +the same concurrency. And the leak axis has its own baseline at 85%, which is the number to +watch for echo work — the clean matrix says nothing about it. + Both mechanisms that consume mic energy were ruled out as causes by disabling them: the hold's VAD extension (`HOLD_VAD_MAX_EXTENSION_SECS = 0`) and the stale-partial watchdog's mic-quiet anchor, separately and together, fail at the same rate. That diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index 4f073aea..16608e1a 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -1,4 +1,69 @@ { + "deepgram-flux/heuristic": { + "label": "deepgram-flux/heuristic", + "stt": "deepgram-flux", + "detector": "heuristic", + "runs": 96, + "passed": 96, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 226.6, + "latency_p95": 343.5, + "latency_min": 174.1, + "latency_max": 1117.8, + "latency_samples": 158, + "dead_air_p50": 557.1, + "dead_air_p95": 1521.7, + "dead_air_samples": 153, + "per_scenario": { + "banking_digits": 1.0, + "banking_digits_pause": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_list_pause": 1.0, + "food_long_pause": 1.0, + "food_pause": 1.0, + "food_rapid_fire": 1.0, + "food_simple": 1.0, + "food_trailing_preposition": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_filler_midway": 1.0, + "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0, + "support_trailing_conjunction": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "coding_double_pause", + "coding_pause", + "food_backchannel", + "medical_hesitant_pause", + "medical_self_correction" + ], + "unexpected_passes": [], + "wall_secs": 799.7, + "jobs": 6 + }, "deepgram-flux/lexical": { "label": "deepgram-flux/lexical", "stt": "deepgram-flux", @@ -8,14 +73,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 273.2, - "latency_p95": 363.9, - "latency_min": 196.0, - "latency_max": 508.2, - "latency_samples": 153, - "dead_air_p50": 717.5, - "dead_air_p95": 2170.2, - "dead_air_samples": 150, + "latency_p50": 228.8, + "latency_p95": 341.3, + "latency_min": 165.8, + "latency_max": 550.6, + "latency_samples": 152, + "dead_air_p50": 639.9, + "dead_air_p95": 2163.9, + "dead_air_samples": 149, "per_scenario": { "banking_correction": 1.0, "banking_digits": 1.0, @@ -61,7 +126,7 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 828.4, + "wall_secs": 846.0, "jobs": 6 }, "deepgram-flux/local": { @@ -73,14 +138,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 280.4, - "latency_p95": 364.0, - "latency_min": 198.6, - "latency_max": 442.2, - "latency_samples": 151, - "dead_air_p50": 750.0, - "dead_air_p95": 1945.9, - "dead_air_samples": 147, + "latency_p50": 219.2, + "latency_p95": 300.4, + "latency_min": 167.8, + "latency_max": 414.3, + "latency_samples": 145, + "dead_air_p50": 638.5, + "dead_air_p95": 1930.4, + "dead_air_samples": 141, "per_scenario": { "banking_digits": 1.0, "banking_digits_pause": 1.0, @@ -126,7 +191,7 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 838.0, + "wall_secs": 851.7, "jobs": 6 }, "deepgram-flux/local[leak=0.15]": { @@ -211,18 +276,18 @@ "stt": "deepgram-flux", "detector": "provider", "runs": 81, - "passed": 81, - "pass_rate": 1.0, - "ghost_turns": 0, + "passed": 80, + "pass_rate": 0.9876543209876543, + "ghost_turns": 1, "errors": 0, - "latency_p50": 275.1, - "latency_p95": 386.9, - "latency_min": 191.8, - "latency_max": 477.2, - "latency_samples": 162, - "dead_air_p50": 554.2, - "dead_air_p95": 1262.7, - "dead_air_samples": 157, + "latency_p50": 223.1, + "latency_p95": 329.4, + "latency_min": 169.5, + "latency_max": 383.9, + "latency_samples": 158, + "dead_air_p50": 496.4, + "dead_air_p95": 1481.3, + "dead_air_samples": 151, "per_scenario": { "banking_digits": 1.0, "banking_short_reject": 1.0, @@ -240,7 +305,7 @@ "medical_barge_in": 1.0, "medical_barge_in_twice": 1.0, "medical_long_utterance": 1.0, - "medical_simple": 1.0, + "medical_simple": 0.6666666666666666, "support_barge_in": 1.0, "support_barge_in_instant": 1.0, "support_barge_in_late": 1.0, @@ -252,7 +317,9 @@ "support_simple": 1.0, "support_trailing_conjunction": 1.0 }, - "flaky": [], + "flaky": [ + "medical_simple" + ], "known_failures": [ "banking_confirmation", "banking_correction", @@ -266,7 +333,72 @@ "support_pause_short" ], "unexpected_passes": [], - "wall_secs": 783.1, + "wall_secs": 768.9, + "jobs": 6 + }, + "deepgram-nova/heuristic": { + "label": "deepgram-nova/heuristic", + "stt": "deepgram-nova", + "detector": "heuristic", + "runs": 72, + "passed": 72, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 213.5, + "latency_p95": 299.8, + "latency_min": 164.7, + "latency_max": 412.6, + "latency_samples": 189, + "dead_air_p50": 523.9, + "dead_air_p95": 735.2, + "dead_air_samples": 180, + "per_scenario": { + "banking_digits": 1.0, + "banking_digits_pause": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_rapid_fire": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_hesitation": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "coding_double_pause", + "coding_pause", + "food_backchannel", + "food_list_pause", + "food_pause", + "food_trailing_preposition", + "medical_filler_midway", + "medical_hesitant_pause", + "medical_long_utterance", + "medical_self_correction", + "support_pause", + "support_pause_short", + "support_trailing_conjunction" + ], + "unexpected_passes": [], + "wall_secs": 817.6, "jobs": 6 }, "deepgram-nova/lexical": { @@ -274,25 +406,25 @@ "stt": "deepgram-nova", "detector": "lexical", "runs": 81, - "passed": 81, - "pass_rate": 1.0, + "passed": 80, + "pass_rate": 0.9876543209876543, "ghost_turns": 0, "errors": 0, - "latency_p50": 278.8, - "latency_p95": 370.2, - "latency_min": 193.7, - "latency_max": 388.7, - "latency_samples": 159, - "dead_air_p50": 573.2, - "dead_air_p95": 2086.2, - "dead_air_samples": 155, + "latency_p50": 220.0, + "latency_p95": 307.6, + "latency_min": 165.5, + "latency_max": 428.6, + "latency_samples": 163, + "dead_air_p50": 548.5, + "dead_air_p95": 2067.2, + "dead_air_samples": 154, "per_scenario": { "banking_digits": 1.0, "banking_hesitation": 1.0, "banking_short_reject": 1.0, "coding_barge_in": 1.0, "coding_barge_in_echo": 1.0, - "coding_double_pause": 1.0, + "coding_double_pause": 0.6666666666666666, "coding_followup_after_reply": 1.0, "coding_simple": 1.0, "food_barge_in": 1.0, @@ -315,7 +447,9 @@ "support_silence_only": 1.0, "support_simple": 1.0 }, - "flaky": [], + "flaky": [ + "coding_double_pause" + ], "known_failures": [ "banking_confirmation", "banking_correction", @@ -331,7 +465,7 @@ "support_trailing_conjunction" ], "unexpected_passes": [], - "wall_secs": 815.3, + "wall_secs": 830.8, "jobs": 6 }, "deepgram-nova/local": { @@ -339,30 +473,30 @@ "stt": "deepgram-nova", "detector": "local", "runs": 96, - "passed": 96, - "pass_rate": 1.0, + "passed": 92, + "pass_rate": 0.9583333333333334, "ghost_turns": 0, "errors": 0, - "latency_p50": 274.1, - "latency_p95": 355.9, - "latency_min": 195.4, - "latency_max": 446.6, - "latency_samples": 153, - "dead_air_p50": 661.7, - "dead_air_p95": 1880.4, - "dead_air_samples": 150, + "latency_p50": 224.2, + "latency_p95": 300.5, + "latency_min": 167.0, + "latency_max": 482.6, + "latency_samples": 152, + "dead_air_p50": 645.5, + "dead_air_p95": 2040.2, + "dead_air_samples": 149, "per_scenario": { "banking_digits": 1.0, "banking_hesitation": 1.0, "banking_short_reject": 1.0, "coding_barge_in": 1.0, "coding_barge_in_echo": 1.0, - "coding_double_pause": 1.0, + "coding_double_pause": 0.3333333333333333, "coding_followup_after_reply": 1.0, - "coding_pause": 1.0, + "coding_pause": 0.6666666666666666, "coding_simple": 1.0, "food_barge_in": 1.0, - "food_long_pause": 1.0, + "food_long_pause": 0.6666666666666666, "food_pause": 1.0, "food_rapid_fire": 1.0, "food_simple": 1.0, @@ -385,7 +519,11 @@ "support_simple": 1.0, "support_trailing_conjunction": 1.0 }, - "flaky": [], + "flaky": [ + "coding_double_pause", + "coding_pause", + "food_long_pause" + ], "known_failures": [ "banking_confirmation", "banking_correction", @@ -396,30 +534,158 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 828.1, + "wall_secs": 894.1, + "jobs": 6 + }, + "deepgram-nova/provider": { + "label": "deepgram-nova/provider", + "stt": "deepgram-nova", + "detector": "provider", + "runs": 66, + "passed": 66, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 208.4, + "latency_p95": 288.8, + "latency_min": 158.9, + "latency_max": 379.9, + "latency_samples": 189, + "dead_air_p50": 517.1, + "dead_air_p95": 691.5, + "dead_air_samples": 180, + "per_scenario": { + "banking_digits": 1.0, + "banking_digits_pause": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, + "coding_simple": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_rapid_fire": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "coding_double_pause", + "coding_pause", + "food_backchannel", + "food_list_pause", + "food_pause", + "food_trailing_preposition", + "medical_filler_midway", + "medical_hesitant_pause", + "medical_long_utterance", + "medical_self_correction", + "support_pause", + "support_pause_short", + "support_trailing_conjunction" + ], + "unexpected_passes": [], + "wall_secs": 794.5, + "jobs": 6 + }, + "elevenlabs/heuristic": { + "label": "elevenlabs/heuristic", + "stt": "elevenlabs", + "detector": "heuristic", + "runs": 75, + "passed": 75, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 217.3, + "latency_p95": 313.5, + "latency_min": 164.6, + "latency_max": 429.8, + "latency_samples": 171, + "dead_air_p50": 1477.2, + "dead_air_p95": 1735.0, + "dead_air_samples": 168, + "per_scenario": { + "banking_digits": 1.0, + "banking_hesitation": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, + "coding_simple": 1.0, + "food_backchannel": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_hesitation": 1.0, + "medical_long_utterance": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "banking_digits_pause", + "coding_double_pause", + "coding_pause", + "food_list_pause", + "food_pause", + "food_rapid_fire", + "food_trailing_preposition", + "medical_filler_midway", + "medical_hesitant_pause", + "medical_self_correction", + "support_pause", + "support_trailing_conjunction" + ], + "unexpected_passes": [], + "wall_secs": 899.4, "jobs": 6 }, "elevenlabs/lexical": { "label": "elevenlabs/lexical", "stt": "elevenlabs", "detector": "lexical", - "runs": 32, - "passed": 32, - "pass_rate": 1.0, - "ghost_turns": 1, + "runs": 99, + "passed": 97, + "pass_rate": 0.9797979797979798, + "ghost_turns": 0, "errors": 0, - "latency_p50": 221.0, - "latency_p95": 367.1, - "latency_min": 183.3, - "latency_max": 700.9, - "latency_samples": 47, - "dead_air_p50": 1446.1, - "dead_air_p95": 2911.6, - "dead_air_samples": 47, + "latency_p50": 220.6, + "latency_p95": 309.6, + "latency_min": 169.3, + "latency_max": 491.2, + "latency_samples": 145, + "dead_air_p50": 1478.4, + "dead_air_p95": 2999.4, + "dead_air_samples": 144, "per_scenario": { "banking_correction": 1.0, "banking_digits": 1.0, - "banking_digits_pause": 1.0, + "banking_digits_pause": 0.6666666666666666, "banking_hesitation": 1.0, "banking_short_reject": 1.0, "coding_barge_in": 1.0, @@ -430,9 +696,10 @@ "coding_simple": 1.0, "food_backchannel": 1.0, "food_barge_in": 1.0, + "food_long_pause": 1.0, "food_simple": 1.0, "food_trailing_preposition": 1.0, - "medical_barge_in": 1.0, + "medical_barge_in": 0.6666666666666666, "medical_barge_in_twice": 1.0, "medical_filler_midway": 1.0, "medical_hesitation": 1.0, @@ -450,44 +717,46 @@ "support_silence_only": 1.0, "support_simple": 1.0 }, - "flaky": [], + "flaky": [ + "banking_digits_pause", + "medical_barge_in" + ], "known_failures": [ "banking_confirmation", "food_list_pause", - "food_long_pause", "food_pause", "food_rapid_fire", "medical_hesitant_pause", "support_trailing_conjunction" ], "unexpected_passes": [], - "wall_secs": 311.0, - "jobs": 1 + "wall_secs": 943.9, + "jobs": 6 }, "elevenlabs/local": { "label": "elevenlabs/local", "stt": "elevenlabs", "detector": "local", - "runs": 31, - "passed": 31, - "pass_rate": 1.0, - "ghost_turns": 1, + "runs": 93, + "passed": 90, + "pass_rate": 0.967741935483871, + "ghost_turns": 0, "errors": 0, - "latency_p50": 237.4, - "latency_p95": 337.5, - "latency_min": 178.3, - "latency_max": 558.0, - "latency_samples": 48, - "dead_air_p50": 1523.1, - "dead_air_p95": 2837.7, - "dead_air_samples": 47, + "latency_p50": 234.8, + "latency_p95": 328.8, + "latency_min": 169.5, + "latency_max": 482.6, + "latency_samples": 144, + "dead_air_p50": 1525.4, + "dead_air_p95": 2833.0, + "dead_air_samples": 141, "per_scenario": { "banking_digits": 1.0, "banking_hesitation": 1.0, "banking_short_reject": 1.0, "coding_barge_in": 1.0, "coding_barge_in_echo": 1.0, - "coding_double_pause": 1.0, + "coding_double_pause": 0.6666666666666666, "coding_followup_after_reply": 1.0, "coding_pause": 1.0, "coding_simple": 1.0, @@ -497,7 +766,7 @@ "food_pause": 1.0, "food_simple": 1.0, "medical_barge_in": 1.0, - "medical_barge_in_twice": 1.0, + "medical_barge_in_twice": 0.3333333333333333, "medical_filler_midway": 1.0, "medical_hesitation": 1.0, "medical_long_utterance": 1.0, @@ -514,7 +783,10 @@ "support_simple": 1.0, "support_trailing_conjunction": 1.0 }, - "flaky": [], + "flaky": [ + "coding_double_pause", + "medical_barge_in_twice" + ], "known_failures": [ "banking_confirmation", "banking_correction", @@ -526,7 +798,70 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 309.5, - "jobs": 1 + "wall_secs": 933.8, + "jobs": 6 + }, + "elevenlabs/provider": { + "label": "elevenlabs/provider", + "stt": "elevenlabs", + "detector": "provider", + "runs": 69, + "passed": 69, + "pass_rate": 1.0, + "ghost_turns": 0, + "errors": 0, + "latency_p50": 216.4, + "latency_p95": 302.1, + "latency_min": 166.6, + "latency_max": 340.3, + "latency_samples": 172, + "dead_air_p50": 1480.9, + "dead_air_p95": 1722.1, + "dead_air_samples": 169, + "per_scenario": { + "banking_digits": 1.0, + "banking_short_reject": 1.0, + "coding_barge_in": 1.0, + "coding_barge_in_echo": 1.0, + "coding_followup_after_reply": 1.0, + "coding_simple": 1.0, + "food_backchannel": 1.0, + "food_barge_in": 1.0, + "food_long_pause": 1.0, + "food_simple": 1.0, + "medical_barge_in": 1.0, + "medical_barge_in_twice": 1.0, + "medical_long_utterance": 1.0, + "medical_simple": 1.0, + "support_barge_in": 1.0, + "support_barge_in_instant": 1.0, + "support_barge_in_late": 1.0, + "support_barge_in_one_word": 1.0, + "support_closer": 1.0, + "support_echo_silence": 1.0, + "support_pause_short": 1.0, + "support_silence_only": 1.0, + "support_simple": 1.0 + }, + "flaky": [], + "known_failures": [ + "banking_confirmation", + "banking_correction", + "banking_digits_pause", + "coding_double_pause", + "coding_pause", + "food_list_pause", + "food_pause", + "food_rapid_fire", + "food_trailing_preposition", + "medical_filler_midway", + "medical_hesitant_pause", + "medical_self_correction", + "support_pause", + "support_trailing_conjunction" + ], + "unexpected_passes": [], + "wall_secs": 878.2, + "jobs": 6 } } diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 4d7004c3..68684c66 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -548,6 +548,21 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: # separate from the text-only reason so a fix to one is not credited to the other. _AUDIO_PAUSE_SHORTFALL = "audio EOU hears the continuation but the hold does not survive this gap" +# `heuristic` and `provider` have no HOLD at all, so a pause the STT commits at is a +# turn boundary and nothing downstream can merge it. Not a defect but the control +# group: it measures what the hold path is worth, which is 65-69% against 98-100% on +# the same STT. +# +# Marked per cell rather than per detector, because whether it bites is an STT × +# detector interaction and not a property of either. `deepgram-flux/heuristic` scores +# 90% on the identical detector, since Flux holds the fragment provider-side before +# any detector sees it — so a blanket "holdless detector cannot merge" rule would +# falsely mark nine scenarios it passes and hide regressions there. Nova and +# ElevenLabs commit each fragment, and their two holdless cells fail the same family. +_NO_HOLD_TO_MERGE = ( + "`heuristic` and `provider` have no hold, so each fragment the STT commits becomes its own turn" +) + # ElevenLabs' endpointer waits longer than Flux's, which helps mid-sentence pauses # and hurts here: two finished sentences 0.9s apart come back as one turn, in all # four cells, with no detector given a chance to disagree. @@ -655,6 +670,12 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], + known_failure={ + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, + }, note=( "Used to split under `provider` and `local` and was marked a known failure for " "both. Fluent synthesis fixed it outright: rendered standalone this fragment " @@ -777,7 +798,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: Interrupted(False), NoErrors(), ], - known_failure={"deepgram-flux/provider": _FLUX_PROVIDER_SPLIT}, + known_failure={ + "deepgram-flux/provider": _FLUX_PROVIDER_SPLIT, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, + }, intermittent=True, note=( "The floor of the pause family: 0.6s is shorter than any endpointer's silence " @@ -804,6 +829,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: known_failure={ "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL + " — merged 3/4", + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -884,6 +913,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: known_failure={ "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL + " — merged 2/3", + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, quick=True, @@ -942,6 +975,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", "elevenlabs/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -1011,6 +1048,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: known_failure={ "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -1121,6 +1162,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-flux/*": _TRAILING_MODIFIER_FAILURE, "deepgram-nova/local": _TRAILING_MODIFIER_FAILURE, "elevenlabs/local": _TRAILING_MODIFIER_FAILURE + " — merged 2/3", + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -1147,6 +1192,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: known_failure={ "deepgram-flux/provider": _FLUX_PROVIDER_GHOST_I, "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -1173,7 +1222,9 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: expect=[UserTurns(1), ContentPreserved(min_similarity=0.8), NoGhostTurns(), NoErrors()], known_failure={ "deepgram-nova/lexical": "Nova endpoints at the clause boundaries inside this run-on " - "and text EOU scores each piece finished, so it commits three turns" + "and text EOU scores each piece finished, so it commits three turns", + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, note=( "Twelve seconds of unbroken speech with several clause boundaries an endpointer " @@ -1212,6 +1263,8 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, "elevenlabs/local": _AUDIO_PAUSE_SHORTFALL + " — merged 2/3", + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, }, known_failure_under_leak={_ECHO_LEAK_CELL: _ECHO_GARBLED_DIGITS}, intermittent=True, @@ -1289,6 +1342,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "deepgram-nova/local": _TRAILING_MODIFIER_FAILURE, "deepgram-nova/lexical": _TRAILING_MODIFIER_FAILURE, "elevenlabs/local": _TRAILING_MODIFIER_FAILURE + " — merged 1/3", + "deepgram-flux/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -1325,6 +1383,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: known_failure={ "deepgram-flux/provider": _FLUX_PROVIDER_SPLIT, "deepgram-nova/lexical": _TEXT_ONLY_PAUSE_SHORTFALL, + "deepgram-flux/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( @@ -1379,7 +1442,11 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], known_failure={ "deepgram-flux/*": "holds through the first gap and splits at the second; the " - "fragment it commits reads as a finished sentence, so nothing argues for holding" + "fragment it commits reads as a finished sentence, so nothing argues for holding", + "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, + "elevenlabs/provider": _NO_HOLD_TO_MERGE, + "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, + "deepgram-nova/provider": _NO_HOLD_TO_MERGE, }, intermittent=True, note=( diff --git a/python/tests/voice/test_turn_detection.py b/python/tests/voice/test_turn_detection.py index 76a82c65..9fbeb333 100644 --- a/python/tests/voice/test_turn_detection.py +++ b/python/tests/voice/test_turn_detection.py @@ -128,10 +128,23 @@ def test_verbatim_echo_arms_the_garbled_branch(self) -> None: resemblance is admissible. This is the whole mechanism in three lines.""" detector = HeuristicTurnDetector() state = self._state(self.REPLY) - assert detector.echo_verdict("authorized retailers.", state) + assert detector.echo_verdict("authorized retailers.", state, arm=True) for echo in self.GARBLED: assert detector.echo_verdict(echo, state), echo + def test_a_partial_cannot_arm_the_latch(self) -> None: + """Regression: `food_long_pause` on two cells, 100% -> 0%. + + In a confirmation flow the user's own partials are verbatim substrings of the + reply by construction, so letting a partial count as proof hands the fuzzy + branch a loaded gun and it shoots the commit that follows. Suppressing the + partial itself is fine and predates this; arming on it is not. + """ + detector = HeuristicTurnDetector() + state = self._state("Got it — a large pepperoni pizza.") + assert detector.echo_verdict("pepperoni pizza", state) + assert not detector.echo_verdict("Pepperoni pizza, please.", state) + def test_the_latch_does_not_leak_across_sessions(self) -> None: """Detectors are cloned per session, so proof from one call must not arm another.""" leaking = HeuristicTurnDetector() diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index 71ef0f55..60470062 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -135,7 +135,7 @@ def push_audio(self, chunk: bytes) -> None: # noqa: B027 _echo_leak_seen: bool = False """This session has produced verbatim echo, so its AEC demonstrably leaks.""" - def echo_verdict(self, text: str, state: TurnState) -> bool: + def echo_verdict(self, text: str, state: TurnState, *, arm: bool = False) -> bool: """Whether ``text`` is the assistant hearing itself. Two branches with very different standing. A verbatim substring of what is @@ -165,7 +165,17 @@ def echo_verdict(self, text: str, state: TurnState) -> bool: if not _echo_window_open(state): return False if _likely_stt_echo(text, state.assistant_text): - self._echo_leak_seen = True + # Only a commit is allowed to arm the latch. A partial is text the STT is + # still revising, and reading it as evidence about the *microphone* is a + # category error that costs a turn: in a confirmation flow the user's own + # partials are verbatim substrings of the reply by construction. `Pepperoni` + # then `Pepperoni pizza` against "Got it — a large pepperoni pizza." armed + # the latch on a clean run, and the now-armed resemblance branch ate the + # commit that followed. Length cannot tell those apart either — the echo + # this exists to catch is `memory access` at 13 chars, the false proof is + # `pepperoni pizza` at 15. + if arm: + self._echo_leak_seen = True return True return self._echo_leak_seen and _resembles_stt_echo(text, state.assistant_text) @@ -556,7 +566,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: and not state.holding ): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination") - if self.echo_verdict(text, state): + if self.echo_verdict(text, state, arm=True): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") if _is_unvoiced_hallucination(text, state): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination_no_vad") @@ -699,7 +709,7 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: return CommitDecision(action=CommitAction.IGNORE, text=text, reason="garbage") if _is_hesitation_only(text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hesitation") - if self.echo_verdict(text, state): + if self.echo_verdict(text, state, arm=True): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") if _is_unvoiced_hallucination(text, state): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hallucination_no_vad") From f072c106acfe755d2df739e0ad6ed2d534b735d4 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 20:06:08 +0200 Subject: [PATCH 19/30] voice: hold on trailing correction markers, and re-sweep the EL threshold honestly MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit "Send it to account 447. Sorry." commits with holding=False — both EOU signals score it complete and both are right, so no hold is armed and the correction becomes a second turn. What marks it incomplete is discourse rather than prosody or grammar: the marker announces a retraction. local now holds on a finished sentence plus a trailing marker, on the short tier, since the correction follows within ~300ms and a false positive shouldn't cost 3s. Requiring the sentence-then-marker shape is the safety margin — a bare "Sorry." is a whole turn, "I'm sorry." is an apology. banking_correction 6/6 on flux/local and medical_self_correction 6/6 on nova/local, both previously marked; two markers retired, three downgraded. Deepgram local cells gate at 100%, EL holds its 96.8% baseline, and the scenarios that dipped there never trigger the rule. Found re-sweeping vad_silence_threshold_secs under the fixed harness. 1.2 stays: looked two points behind at --repeat 3, but at 6 the gap is 94% vs 83%, and 0.8 scoring below both neighbours marks the first result as underpowered. The value isn't buying merges generally — it absorbs these corrections before any detector sees them, which is why the defect shows up on Flux and Nova instead. --- benchmarks/voice/README.md | 72 +++++++++++++++++++++++ benchmarks/voice/scenario.py | 18 ++++-- python/tests/voice/test_turn_detection.py | 50 ++++++++++++++++ python/timbal/voice/turn_detection.py | 52 ++++++++++++++++ 4 files changed, 187 insertions(+), 5 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index cb708f01..321f48e1 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -1025,6 +1025,78 @@ the kind of price that stops anyone taking one. What makes it sound is unchanged and unrelated: a baseline records its own concurrency, and latency comparison is declined across a mismatch. +### The provider's patience was hiding a sentence we could have read + +The 1.2s conclusion above was measured against a harness that tore down mid-hold, +which penalises exactly the configurations relying on our holds rather than the +provider's. Re-swept once that was fixed, the aggressive end is nowhere near as bad +as it looked — 0.3 goes from 47% to 77% — and at `--repeat 3` the shipped value +looked barely defensible at all: + +| `vad_silence_threshold_secs` | pause merges | dead air p50 | p95 | +|---|---:|---:|---:| +| 0.3 | 77% | 775ms | 2602ms | +| 0.5 | 83% | 765ms | **2388ms** | +| 0.8 | 73% | 962ms | 2924ms | +| 1.2 (ships) | 85% | 1409ms | 2882ms | + +Two points for 642ms is a trade anyone would take. It is also not real: 0.8 scoring +below both neighbours is the signature of an underpowered measurement, n=78 makes +two points about 1.5 runs, and at `--repeat 6` on `local` alone the gap reopens to +94% against 83%. **1.2 stays.** Worth stating plainly because the tempting version +of this exercise — sweep, take the winner, ship it — would have shipped a 6% merge +regression on the strength of noise, twice, in opposite directions. + +What the tighter sweep bought instead was the *shape* of the disagreement. Nothing +here is a curve; it is two families pulling opposite ways, each pinned at 0% or 100% +across all six repeats: + +| scenario | 0.5 | 0.6 | 0.8 | 1.2 | +|---|---:|---:|---:|---:| +| `medical_self_correction` | 0% | 0% | 0% | 100% | +| `banking_correction` | 0% | 0% | 0% | 100% | +| `food_list_pause` | 100% | 100% | 100% | 17% | + +The two that collapse are the two the hold-tier sweep could never fix at any value, +and the trace says why — with `holding=False`, no hold is armed at all, so there was +never a tier to blame: + +``` +commit 'Send it to account 447. Sorry.' holding=False → new_turn +commit '448.' → new_turn, 2 turns, FAIL +``` + +Both EOU signals score that finished and both are right: it *is* a complete +sentence. What makes it incomplete is neither acoustic nor syntactic but discourse +— "Sorry." and "No, wait." announce a retraction, the way a hedge announces a pause. +So `local` now holds on a finished sentence plus a trailing correction marker +regardless of either score (`trailing_correction_marker`, short tier, since the +correction follows within ~300ms by nature and a false positive should not cost 3s). +The sentence-then-marker *shape* is the entire safety margin: a bare "Sorry." is +somebody's whole turn, and "I'm sorry." is an apology. + +Measured at `--repeat 6`, at the shipped 1.2, against cells where both scenarios +were marked known failures: + +| | `flux/local` | `nova/local` | `elevenlabs/local` | +|---|---:|---:|---:| +| `banking_correction` | **6/6** | 4/6 | 5/6 | +| `medical_self_correction` | 0/6 | **6/6** | 5/6 | + +Two markers retired outright and three downgraded to a race the hold either wins or +loses. Both Deepgram cells gate at 100%; ElevenLabs holds its 96.8% baseline, and +the three scenarios that dipped to 2/3 there never trigger the rule once across 9 +runs, so they are the provider variance documented above. It reaches only `local` — +`LexicalTurnDetector` is a sibling of `LocalAudioTurnDetector`, not a subclass — so +the improvements visible on `lexical` cells in the same runs are not this change, +which is its own hint that some markers there are stale. + +The threshold question is now a different one. ElevenLabs' 1.2s is not buying +merges in general, it is buying *these* merges, by absorbing corrections before any +detector sees them — which is why the defect surfaced on Flux and Nova instead. Each +such case read at the detector is 630ms of dead air per turn that stops needing to +be bought. + ## Running ```bash diff --git a/benchmarks/voice/scenario.py b/benchmarks/voice/scenario.py index 68684c66..c5ec37d5 100644 --- a/benchmarks/voice/scenario.py +++ b/benchmarks/voice/scenario.py @@ -534,6 +534,16 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: "its hold to 0.35s" ) +# The announced half of the family above: "...447. Sorry." and "...blue pill. No, wait." +# say outright that a correction is coming, and `local` now holds on that marker alone +# (trailing_correction_marker). What remains here is timing, not judgement — the hold is +# armed, and the correction either arrives inside it or does not. Retired the markers on +# flux/local (banking, 6/6) and nova/local (medical, 6/6) outright. +_CORRECTION_MARKER_HELD = ( + "the correction marker now arms a hold, so this is a race rather than a misjudgement: " + "the retraction has to arrive inside the short tier" +) + # Off Flux, Namo alone is not enough to hold a mid-sentence pause. Nova commits a # fragment that reads as a finished sentence and `lexical` has no second opinion to # contradict it — the audio EOU is exactly what `local` adds, and the gap between @@ -1160,8 +1170,7 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: ], known_failure={ "deepgram-flux/*": _TRAILING_MODIFIER_FAILURE, - "deepgram-nova/local": _TRAILING_MODIFIER_FAILURE, - "elevenlabs/local": _TRAILING_MODIFIER_FAILURE + " — merged 2/3", + "elevenlabs/local": _CORRECTION_MARKER_HELD + " — merged 5/6", "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, "elevenlabs/provider": _NO_HOLD_TO_MERGE, "deepgram-nova/heuristic": _NO_HOLD_TO_MERGE, @@ -1337,11 +1346,10 @@ def fluent_groups(self) -> list[tuple[str, tuple[str, ...]]]: NoErrors(), ], known_failure={ - "deepgram-flux/local": _TRAILING_MODIFIER_FAILURE, "deepgram-flux/provider": _TRAILING_MODIFIER_FAILURE, - "deepgram-nova/local": _TRAILING_MODIFIER_FAILURE, + "deepgram-nova/local": _CORRECTION_MARKER_HELD + " — merged 4/6", "deepgram-nova/lexical": _TRAILING_MODIFIER_FAILURE, - "elevenlabs/local": _TRAILING_MODIFIER_FAILURE + " — merged 1/3", + "elevenlabs/local": _CORRECTION_MARKER_HELD + " — merged 5/6", "deepgram-flux/heuristic": _NO_HOLD_TO_MERGE, "elevenlabs/heuristic": _NO_HOLD_TO_MERGE, "elevenlabs/provider": _NO_HOLD_TO_MERGE, diff --git a/python/tests/voice/test_turn_detection.py b/python/tests/voice/test_turn_detection.py index 9fbeb333..0af321f5 100644 --- a/python/tests/voice/test_turn_detection.py +++ b/python/tests/voice/test_turn_detection.py @@ -27,6 +27,7 @@ SemanticTurnDetector, TurnDetector, TurnState, + _ends_with_correction_marker, _is_garbage_commit, _is_same_user_utterance_refinement, _is_unvoiced_hallucination, @@ -34,6 +35,41 @@ resolve_turn_detector, ) + +class TestTrailingCorrectionMarker: + """A finished sentence plus "Sorry." is the one incompleteness no EOU model sees. + + Both signals score these complete and both are right about the sentence — the + speaker is simply not done. The shape requirement is the whole safety margin, so + the negatives matter more than the positives here. + """ + + def test_correction_after_a_finished_sentence(self) -> None: + for text in ( + "Send it to account 447. Sorry.", + "I take the blue pill. No, wait.", + "Book it for Tuesday. Actually.", + "The total is 40. Hold on.", + ): + assert _ends_with_correction_marker(text), text + + def test_a_bare_marker_is_a_whole_turn(self) -> None: + """Holding these buys nothing and costs dead air: there is no sentence in front + of the marker, so nothing is being corrected.""" + for text in ("Sorry.", "Wait, hold on.", "Actually, cancel that.", "Hold on."): + assert not _ends_with_correction_marker(text), text + + def test_marker_words_inside_a_sentence_do_not_count(self) -> None: + """An apology is not a retraction, and "Actually, Wednesday." is the correction + itself rather than the announcement of one.""" + for text in ( + "I'm sorry.", + "Book it for Tuesday. Actually, Wednesday.", + "I need help with my recent order.", + "What is your return policy?", + ): + assert not _ends_with_correction_marker(text), text + from .test_session import MockSTT, MockTTS @@ -724,6 +760,20 @@ async def test_complete_audio_new_turn(self) -> None: assert decision.action is CommitAction.NEW_TURN await det.close() + async def test_trailing_correction_holds_despite_both_signals_complete(self) -> None: + """`banking_correction` and `medical_self_correction`, marked on five and four + cells: audio scores 0.9, the text is a finished sentence, and the correction that + follows becomes a second turn. Nothing else in the detector can catch it, because + nothing else is wrong — the sentence really is complete.""" + det = LocalAudioTurnDetector(audio_eou=_FixedAudioEou(0.9)) + await det.start(type("C", (), {"sample_rate": 16000})()) + det.push_audio(b"\x00\x01" * 8000) + decision = await det.on_committed("Send it to account 447. Sorry.", _state()) + assert decision.action is CommitAction.HOLD + assert decision.reason == "trailing_correction_marker" + assert decision.hold_timeout_secs == det.text_incomplete_hold_timeout_secs + await det.close() + async def test_short_audio_incomplete_text_holds(self) -> None: """< 0.5s of buffered PCM must not pass an incomplete utterance through as NEW_TURN — the lexical fallback holds it (audio model never called).""" diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index 60470062..e8483e84 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -479,6 +479,38 @@ def _looks_like_fresh_hold_utterance(text: str) -> bool: return True +_CORRECTION_MARKERS = frozenset( + {"sorry", "no wait", "oh wait", "wait", "actually", "i mean", "scratch that", "my bad", "hold on"} +) +_TRAILING_MARKER_RE = re.compile(r"^(?P.*[.!?])\s*(?P[^.!?]+[.!?]?)$", re.S) + + +def _ends_with_correction_marker(text: str) -> bool: + """A finished sentence with a self-correction marker stuck on the end. + + The one case no end-of-utterance model can resolve, because there is nothing to + resolve: "Send it to account 447. Sorry." and "I take the blue pill. No, wait." + are complete sentences, both EOU signals correctly score them finished, and the + speaker is nonetheless mid-thought. What gives it away is discourse, not prosody + or syntax — "Sorry." announces a correction the way a hedge announces a pause, + which is the same kind of lexical cue :func:`_is_hesitation_only` already reads. + + Deliberately requires the sentence-then-marker *shape* rather than just a marker + at the end. A bare "Sorry." is a whole turn and holding it only adds dead air, + and "I'm sorry." is an apology rather than a retraction — both fail the head test. + + Found because ElevenLabs hides it: at `vad_silence_threshold_secs=1.2` the provider + merges the correction into one commit before any detector sees it, so the defect is + invisible there and shows up on Flux and Nova instead. That masking is also what the + 1.2s default is buying, at ~630ms of dead air on every turn. + """ + m = _TRAILING_MARKER_RE.match(text.strip()) + if m is None: + return False + tail = " ".join(_WORD_RE.findall(m.group("tail"))).lower() + return tail in _CORRECTION_MARKERS + + _TERMINAL_END_CHARS = frozenset(".?!。？！") @@ -1132,6 +1164,18 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: reason="audio_complete_text_incomplete", hold_timeout_secs=min(self.text_incomplete_hold_timeout_secs, self.hold_timeout_secs), ) + if _ends_with_correction_marker(candidate): + # Both signals say finished and both are right about the sentence; the + # marker says the speaker is not. Held on the short tier because a + # correction follows within a few hundred ms by nature — measured at + # ~300ms — so the long hold buys nothing and would cost 3s whenever + # the marker misleads. + return CommitDecision( + action=CommitAction.HOLD, + text=candidate, + reason="trailing_correction_marker", + hold_timeout_secs=min(self.text_incomplete_hold_timeout_secs, self.hold_timeout_secs), + ) return CommitDecision( action=CommitAction.NEW_TURN, text=candidate, @@ -1163,6 +1207,14 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: if p_text is not None and p_text >= self.TEXT_COMPLETE_TIER_THRESHOLD: timeout = min(self.text_complete_hold_timeout_secs, self.hold_timeout_secs) reason = "audio_hold_text_complete" + logger.debug( + "audio_hold_tier", + p_audio=round(p, 3), + p_text=None if p_text is None else round(p_text, 3), + timeout_secs=timeout, + reason=reason, + text_preview=candidate[:60], + ) return CommitDecision( action=CommitAction.HOLD, text=candidate, From 40d38f5b381562036eed42eb20eaf8c4f98b17d3 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 21:11:15 +0200 Subject: [PATCH 20/30] voice: measure Flux's end-of-turn threshold, and drop one-word ghosts MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit provider has no hold, so on Flux eot_threshold *is* the turn policy — the only setting that can merge a pause there, in the pairing Flux exists for. We shipped Deepgram's default and measured only eot_timeout_ms. Swept over the pause family it is a clean monotonic curve, unlike ElevenLabs': 46% / 68% / 82% / 91% merges at 0.6 / 0.7 / 0.8 / 0.9, for 448 / 635 / 859 / 1944ms of dead air. 0.8 buys fourteen points for 214ms; 0.9 buys nine more for a second and is slower than ElevenLabs. All four Flux cells now gate at 100% with zero ghosts, re-baselined. The patience introduced a ghost mode: a stray 'I' committing its own turn after a finished one, because Flux holds the turn open long enough to transcribe the trailing audio and a holdless detector takes it. It slipped past _is_garbage_commit (alphanumeric) and _is_unvoiced_hallucination (the user really had just spoken); a one-word commit needs neither test. _is_contentless_single_token drops function words that cannot be an utterance, and not the one-word turns that carry intent — banking_short_reject is the single word "No." Also found: eot_threshold=0.4 is rejected with a 400 and the harness scored 78 session errors as a 0% row rather than reporting invalid config; banking_correction is 0% at every threshold, so that marker is structural; and Flux hears "no wait" as "no weight", which explains medical_self_correction there without reference to holds. --- benchmarks/voice/README.md | 51 +++++++++++++ benchmarks/voice/baseline.json | 90 +++++++++++------------ python/tests/voice/test_turn_detection.py | 29 ++++++++ python/timbal/voice/deepgram.py | 9 +++ python/timbal/voice/turn_detection.py | 23 ++++++ 5 files changed, 156 insertions(+), 46 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 321f48e1..553dac59 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -1097,6 +1097,57 @@ detector sees them — which is why the defect surfaced on Flux and Nova instead such case read at the detector is 630ms of dead air per turn that stops needing to be bought. +### Flux's own threshold was never ours to leave alone + +`provider` has no hold, so on Flux `eot_threshold` *is* the turn policy — it is the +only setting in the pipeline that can merge a pause there, and `provider` is the +pairing Flux exists for. We shipped Deepgram's default and overrode only +`eot_timeout_ms`, which is the ElevenLabs situation again: a number governing +turn-taking, in our config, with nobody's measurement behind it. + +Unlike the ElevenLabs sweep this one is a curve, monotonic in both columns: + +| `eot_threshold` | pause merges | dead air p50 | p95 | +|---|---:|---:|---:| +| 0.4 | *rejected: HTTP 400* | — | — | +| 0.6 | 46% | 448ms | 1409ms | +| 0.7 (Deepgram's default) | 68% | 635ms | 1034ms | +| **0.8 (now ships)** | **82%** | 859ms | 1538ms | +| 0.9 | 91% | 1944ms | 2386ms | + +0.8 buys fourteen points for 214ms; 0.9 buys nine more for a further second and lands +at worse dead air than ElevenLabs, which is the point at which you have stopped tuning +and started choosing to be slow. 0.7→0.8 is what carries `coding_double_pause` +(17%→100%), `banking_digits_pause` (83%→100%) and `medical_hesitant_pause` (17%→67%). +All four Flux cells now gate at 100% with zero ghost turns, dead air p50 677–885ms. + +`banking_correction` is 0% at *every* threshold, which is worth more than the ones +that moved: the lever cannot reach it, so its marker on `flux/provider` is structural +rather than untuned. And `medical_self_correction` fails on Flux because Flux +transcribes "no wait" as **"no weight"** — no correction-marker rule can fire on a +word the STT never produces, which explains that cell without reference to holds at +all. + +Two things fell out of confirming it. Deepgram rejects `eot_threshold=0.4` with a +400, and the harness passed it through and scored 78 session errors as a 0% row +instead of reporting invalid config — a sweep can currently spend seven minutes +measuring nothing. And at 0.8 a stray `'I'` began committing its own turn after a +finished one on `flux/heuristic`: a more patient threshold holds the turn open long +enough for Flux to transcribe something in the trailing audio, and a holdless +detector takes it. That is a ghost turn, the worst class the suite has, and it slipped +between both existing filters — `_is_garbage_commit` requires non-alphanumeric, and +`_is_unvoiced_hallucination` requires Silero to have heard nothing, whereas here the +user genuinely had just spoken. A one-word commit needs neither test: +`_is_contentless_single_token` drops a closed class of function words that cannot be +an utterance ("I", "a", "the", "of", "to", "my"), and deliberately not the one-word +turns that carry intent — `banking_short_reject` *is* the single word "No." + +Unexploited, and the obvious way to stop paying the 214ms: Flux emits +`EagerEndOfTurn` and `TurnResumed`, and `deepgram.py` only logs them. A patient +threshold plus starting the reply on the eager event would let the LLM work during +the window Flux spends confirming, which is dead air currently buying nothing but +confidence. + ## Running ```bash diff --git a/benchmarks/voice/baseline.json b/benchmarks/voice/baseline.json index 16608e1a..dd8a3c9f 100644 --- a/benchmarks/voice/baseline.json +++ b/benchmarks/voice/baseline.json @@ -8,14 +8,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 226.6, - "latency_p95": 343.5, - "latency_min": 174.1, - "latency_max": 1117.8, - "latency_samples": 158, - "dead_air_p50": 557.1, - "dead_air_p95": 1521.7, - "dead_air_samples": 153, + "latency_p50": 222.6, + "latency_p95": 317.1, + "latency_min": 166.4, + "latency_max": 428.0, + "latency_samples": 146, + "dead_air_p50": 677.2, + "dead_air_p95": 1530.7, + "dead_air_samples": 143, "per_scenario": { "banking_digits": 1.0, "banking_digits_pause": 1.0, @@ -61,7 +61,7 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 799.7, + "wall_secs": 823.0, "jobs": 6 }, "deepgram-flux/lexical": { @@ -73,14 +73,14 @@ "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 228.8, - "latency_p95": 341.3, - "latency_min": 165.8, - "latency_max": 550.6, - "latency_samples": 152, - "dead_air_p50": 639.9, - "dead_air_p95": 2163.9, - "dead_air_samples": 149, + "latency_p50": 219.1, + "latency_p95": 311.0, + "latency_min": 169.4, + "latency_max": 397.6, + "latency_samples": 148, + "dead_air_p50": 859.0, + "dead_air_p95": 2345.1, + "dead_air_samples": 144, "per_scenario": { "banking_correction": 1.0, "banking_digits": 1.0, @@ -126,27 +126,28 @@ "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 846.0, + "wall_secs": 861.2, "jobs": 6 }, "deepgram-flux/local": { "label": "deepgram-flux/local", "stt": "deepgram-flux", "detector": "local", - "runs": 99, - "passed": 99, + "runs": 102, + "passed": 102, "pass_rate": 1.0, "ghost_turns": 0, "errors": 0, - "latency_p50": 219.2, - "latency_p95": 300.4, - "latency_min": 167.8, - "latency_max": 414.3, - "latency_samples": 145, - "dead_air_p50": 638.5, - "dead_air_p95": 1930.4, - "dead_air_samples": 141, + "latency_p50": 226.4, + "latency_p95": 310.6, + "latency_min": 173.0, + "latency_max": 394.0, + "latency_samples": 146, + "dead_air_p50": 884.7, + "dead_air_p95": 2146.4, + "dead_air_samples": 143, "per_scenario": { + "banking_correction": 1.0, "banking_digits": 1.0, "banking_digits_pause": 1.0, "banking_hesitation": 1.0, @@ -184,14 +185,13 @@ "flaky": [], "known_failures": [ "banking_confirmation", - "banking_correction", "coding_double_pause", "food_backchannel", "medical_hesitant_pause", "medical_self_correction" ], "unexpected_passes": [], - "wall_secs": 851.7, + "wall_secs": 869.6, "jobs": 6 }, "deepgram-flux/local[leak=0.15]": { @@ -276,18 +276,18 @@ "stt": "deepgram-flux", "detector": "provider", "runs": 81, - "passed": 80, - "pass_rate": 0.9876543209876543, - "ghost_turns": 1, + "passed": 81, + "pass_rate": 1.0, + "ghost_turns": 0, "errors": 0, - "latency_p50": 223.1, - "latency_p95": 329.4, - "latency_min": 169.5, - "latency_max": 383.9, - "latency_samples": 158, - "dead_air_p50": 496.4, - "dead_air_p95": 1481.3, - "dead_air_samples": 151, + "latency_p50": 218.2, + "latency_p95": 336.6, + "latency_min": 174.5, + "latency_max": 655.3, + "latency_samples": 146, + "dead_air_p50": 685.9, + "dead_air_p95": 1837.1, + "dead_air_samples": 143, "per_scenario": { "banking_digits": 1.0, "banking_short_reject": 1.0, @@ -305,7 +305,7 @@ "medical_barge_in": 1.0, "medical_barge_in_twice": 1.0, "medical_long_utterance": 1.0, - "medical_simple": 0.6666666666666666, + "medical_simple": 1.0, "support_barge_in": 1.0, "support_barge_in_instant": 1.0, "support_barge_in_late": 1.0, @@ -317,9 +317,7 @@ "support_simple": 1.0, "support_trailing_conjunction": 1.0 }, - "flaky": [ - "medical_simple" - ], + "flaky": [], "known_failures": [ "banking_confirmation", "banking_correction", @@ -333,7 +331,7 @@ "support_pause_short" ], "unexpected_passes": [], - "wall_secs": 768.9, + "wall_secs": 799.7, "jobs": 6 }, "deepgram-nova/heuristic": { diff --git a/python/tests/voice/test_turn_detection.py b/python/tests/voice/test_turn_detection.py index 0af321f5..40ea4374 100644 --- a/python/tests/voice/test_turn_detection.py +++ b/python/tests/voice/test_turn_detection.py @@ -28,6 +28,7 @@ TurnDetector, TurnState, _ends_with_correction_marker, + _is_contentless_single_token, _is_garbage_commit, _is_same_user_utterance_refinement, _is_unvoiced_hallucination, @@ -36,6 +37,34 @@ ) +class TestContentlessSingleToken: + """A lone function word is a fragment; a lone "No." is an answer. + + The negatives are the point. `banking_short_reject` is a turn consisting of the + single word "No.", so a filter that keys on length alone would delete a scenario. + """ + + def test_bare_function_words_are_dropped(self) -> None: + for text in ("I", "I.", "the", "A.", "my", "To."): + assert _is_contentless_single_token(text), text + + def test_meaningful_one_word_turns_survive(self) -> None: + for text in ("No.", "Yes.", "Stop.", "Wait.", "And?", "So?", "Okay.", "You?"): + assert not _is_contentless_single_token(text), text + + def test_a_function_word_inside_an_utterance_survives(self) -> None: + for text in ("I need help.", "The blue one.", "To account 448."): + assert not _is_contentless_single_token(text), text + + async def test_provider_ignores_a_lone_pronoun(self) -> None: + """Observed on flux/heuristic: 'I' committing its own turn after a finished one, + which is a ghost turn — the assistant answers a word the user did not say.""" + det = ProviderTurnDetector() + decision = await det.on_committed("I", _state()) + assert decision.action is CommitAction.IGNORE + assert decision.reason == "contentless" + + class TestTrailingCorrectionMarker: """A finished sentence plus "Sorry." is the one incompleteness no EOU model sees. diff --git a/python/timbal/voice/deepgram.py b/python/timbal/voice/deepgram.py index 8ae3a304..7fd39cfe 100644 --- a/python/timbal/voice/deepgram.py +++ b/python/timbal/voice/deepgram.py @@ -267,6 +267,15 @@ def _build_uri(self, config: AudioInputConfig) -> str: # EndOfTurn; keep this under the session stale window (2.5s). if "eot_timeout_ms" not in extra: params.append(("eot_timeout_ms", "2000")) + # Deepgram's 0.7 ends a turn on a mid-sentence pause: swept over the + # pause-merge family, it merges 68% against 82% at 0.8 and 91% at 0.9, + # monotonically, for 635ms / 859ms / 1944ms of dead air. 0.8 buys fourteen + # points for 214ms and takes the cell to 100% with no ghost turns; 0.9 buys + # nine more for a further second, which is worse dead air than ElevenLabs. + # `provider` has no hold of its own, so on Flux this value *is* the turn + # policy — it is the only setting that can merge a pause there. + if "eot_threshold" not in extra: + params.append(("eot_threshold", "0.8")) for k, v in extra.items(): if v is None or k.startswith("_") or k not in _FLUX_QUERY_KEYS: continue diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index e8483e84..6e1fa01c 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -307,6 +307,25 @@ def _normalize_echo(s: str) -> str: # silence are one- and two-word stock phrases — "Yes.", "Yeah.", "Okay." — while the # short barge-ins worth protecting run longer ("Wait, hold on.", "Actually, cancel # that.") and carry mic energy regardless. Two words leaves margin on both sides. +# Single tokens that cannot be a whole turn, whatever the mic heard. +# +# Deliberately excludes every one-word utterance that *is* a turn — "No.", "Yes.", +# "Stop.", "Wait.", "And?", "So?" all carry intent and `banking_short_reject` is +# literally "No." What remains is a closed class of function words that cannot stand +# alone: either the first word of an utterance the STT cut off, or the likeliest token +# for a breath. Observed as `'I'` committing its own turn after a finished one on +# `deepgram-flux/heuristic` (`banking_digits_pause`, `banking_short_reject`), which +# neither :func:`_is_garbage_commit` (alphanumeric) nor +# :func:`_is_unvoiced_hallucination` (the user really had just spoken) can reach. +_CONTENTLESS_SINGLE_TOKENS = frozenset({"i", "a", "an", "the", "of", "to", "my"}) + + +def _is_contentless_single_token(text: str) -> bool: + """One function word, alone: a fragment or a mis-transcribed breath, never a turn.""" + words = _WORD_RE.findall(text) + return len(words) == 1 and words[0].lower() in _CONTENTLESS_SINGLE_TOKENS + + MAX_UNVOICED_COMMIT_WORDS = 2 @@ -585,6 +604,8 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: return CommitDecision(action=CommitAction.IGNORE, text=text, reason="garbage") if _is_hesitation_only(text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hesitation") + if _is_contentless_single_token(text): + return CommitDecision(action=CommitAction.IGNORE, text=text, reason="contentless") # A long commit with zero preceding partials while nothing is playing is # almost always an STT hallucination on silence. Uses assistant_active # only — pending HOLD must not flip that flag (see TurnState.holding). @@ -741,6 +762,8 @@ async def on_committed(self, text: str, state: TurnState) -> CommitDecision: return CommitDecision(action=CommitAction.IGNORE, text=text, reason="garbage") if _is_hesitation_only(text): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="hesitation") + if _is_contentless_single_token(text): + return CommitDecision(action=CommitAction.IGNORE, text=text, reason="contentless") if self.echo_verdict(text, state, arm=True): return CommitDecision(action=CommitAction.IGNORE, text=text, reason="echo") if _is_unvoiced_hallucination(text, state): From f28e0718641f6369d7a847f18d642ee93c55c578 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 21:37:05 +0200 Subject: [PATCH 21/30] bench(voice): tell a refused configuration apart from a bad result MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --stt-param eot_threshold=0.4 is outside Flux's accepted range, so every session died on the handshake and the sweep scored 78 refusals as a 0% row — indistinguishable from a setting that merely merges nothing. SWEEPABLE_STT_KEYS validates key names; encoding each provider's ranges beside them would go stale the first time one changed theirs, and would only catch the values we thought to guess. Noticing the refusal catches all of them. config_rejection matches a 4xx on the handshake, and only 4xx: that is deterministic for a given config, while a timeout or 5xx is the transient the repeats average over. The sweep stops scheduling the value, prints the provider's message in place of the row and "-" instead of "0%" per scenario, exits 1. cli.py reports the cell as refused before scoring, so it cannot be baselined or gated against, exits 2. Partial refusals still score the runs that connected. --- benchmarks/voice/README.md | 15 ++++++++++++--- benchmarks/voice/cli.py | 19 ++++++++++++++++++- benchmarks/voice/harness.py | 26 +++++++++++++++++++++++++- benchmarks/voice/sweep.py | 18 ++++++++++++++++-- 4 files changed, 71 insertions(+), 7 deletions(-) diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index 553dac59..d1ebf698 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -1129,9 +1129,18 @@ word the STT never produces, which explains that cell without reference to holds all. Two things fell out of confirming it. Deepgram rejects `eot_threshold=0.4` with a -400, and the harness passed it through and scored 78 session errors as a 0% row -instead of reporting invalid config — a sweep can currently spend seven minutes -measuring nothing. And at 0.8 a stray `'I'` began committing its own turn after a +400, and the harness passed it through and scored 78 refused sessions as a 0% row — +indistinguishable, in the table above, from a setting that merely merges nothing. +`SWEEPABLE_STT_KEYS` validates key *names*, and encoding each provider's accepted +ranges beside them would go stale the first time one changed theirs; noticing the +refusal does not. `config_rejection` now matches a 4xx on the handshake — and only +4xx, since a rejected handshake is deterministic for a given config while a timeout +or a 5xx is the transient the repeats exist to average over. The sweep stops +scheduling that value and prints the provider's message where the row would go, with +`-` rather than `0%` in the per-scenario table; `cli.py` reports the cell as refused +before scoring, so it cannot be baselined or gated against, and exits 2. The cost was +never the six seconds of wasted runtime — it was a number in a results table that +looked like a measurement. And at 0.8 a stray `'I'` began committing its own turn after a finished one on `flux/heuristic`: a more patient threshold holds the turn open long enough for Flux to transcribe something in the trailing audio, and a holdless detector takes it. That is a ghost turn, the worst class the suite has, and it slipped diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index be93beae..4995b88d 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -39,7 +39,7 @@ import structlog from dotenv import load_dotenv -from harness import HarnessConfig, RunResult, coerce_param, run_scenario +from harness import HarnessConfig, RunResult, coerce_param, config_rejection, run_scenario from scenario import SCENARIOS, Scenario, select from score import ( RunRecord, @@ -289,6 +289,23 @@ def log(kind: str, detail: str = "") -> None: cell_records = [r for r in records if r.label == config.label] if not cell_records: continue + # A cell whose every session was refused measured nothing, and a scorecard + # would present that as behaviour: `--stt-param eot_threshold=0.4` is outside + # Flux's range and reads as a plain 0% cell. Reported before scoring so it + # cannot be baselined or gated against. + refused = [why for r in cell_records if (why := config_rejection(r.errors))] + if refused: + print(f"\n{'─' * 72}") + every = len(refused) == len(cell_records) + scope = "every run" if every else f"{len(refused)}/{len(cell_records)} runs" + print(f"{config.label}: {scope} refused by the provider") + for why in sorted(set(refused)): + print(f" {why}") + exit_code = max(exit_code, 2) + # Partial refusals still say something about the runs that connected; + # a cell where none did has no behaviour to score. + if every: + continue card = build_scorecard(cell_records) cards.append(card) diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 167011fd..5782c2ad 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -20,9 +20,10 @@ import array import asyncio +import re import time from collections import deque -from collections.abc import AsyncIterator, Callable, Mapping +from collections.abc import AsyncIterator, Callable, Mapping, Sequence from contextlib import aclosing from dataclasses import dataclass, field from typing import Any @@ -277,6 +278,29 @@ async def stream(self) -> AsyncIterator[bytes]: } +_HANDSHAKE_REJECTION = re.compile(r"server rejected WebSocket connection: HTTP (4\d\d)") + + +def config_rejection(errors: Sequence[str]) -> str | None: + """The provider refused the configuration, as opposed to the run going badly. + + ``SWEEPABLE_STT_KEYS`` validates key *names*, so a value the provider rejects + still runs: `eot_threshold=0.4` is outside Flux's accepted range and every + session dies on the handshake, which the sweep then reported as a 0% row + indistinguishable from a setting that merely merges nothing. Encoding each + provider's accepted ranges here would go stale the first time one changed + theirs; noticing the refusal does not. + + Only 4xx. A rejected handshake is deterministic for a given config, so + repeating it 77 more times cannot learn anything — whereas a timeout or a 5xx + is exactly the transient the repeats exist to average over. + """ + for e in errors: + if m := _HANDSHAKE_REJECTION.search(e): + return f"provider rejected the connection (HTTP {m.group(1)}): {e}" + return None + + def coerce_param(raw: str) -> float | int | bool | str: """Best-effort literal from a command-line value (`0.3` -> float, `true` -> bool).""" for cast in (int, float): diff --git a/benchmarks/voice/sweep.py b/benchmarks/voice/sweep.py index 1da60a5f..11600bae 100644 --- a/benchmarks/voice/sweep.py +++ b/benchmarks/voice/sweep.py @@ -45,7 +45,7 @@ import structlog from dotenv import load_dotenv -from harness import HarnessConfig, coerce_param, run_scenario +from harness import HarnessConfig, coerce_param, config_rejection, run_scenario from scenario import SCENARIOS, Merged, Scenario from synth import synthesize_clips, synthesize_fluent @@ -128,10 +128,17 @@ async def main() -> int: outcomes = {str(v): Outcome(value=str(v)) for v in values} started = time.monotonic() + rejected: dict[str, str] = {} + async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: + if str(value) in rejected: + return config = HarnessConfig(stt=stt, detector=det, **{param_field: {param_key: value}}) async with semaphore: result = await run_scenario(scenario, clips, config) + if why := config_rejection(result.errors): + rejected.setdefault(str(value), why) + return out = outcomes[str(value)] out.total += 1 out.passed += result.passed @@ -157,6 +164,9 @@ async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: print(f"{args.param:>10} {'merges':<10} {'':>4} {'dead air p50':>10} {'p95':>6}") for value in values: + if why := rejected.get(str(value)): + print(f" {value!s:>10} {why}") + continue print(" " + outcomes[str(value)].summary()) print("\nper scenario (pass rate across cells and repeats)\n") @@ -165,6 +175,9 @@ async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: for scenario in scenarios: row = "" for value in values: + if str(value) in rejected: + row += f"{'-':>8} " + continue runs_ = outcomes[str(value)].per_scenario.get(scenario.id, []) row += f"{(sum(runs_) / len(runs_) if runs_ else 0):>8.0%} " print(f" {scenario.id:<30}{row}") @@ -172,7 +185,8 @@ async def one(value: object, stt: str, det: str, scenario: Scenario) -> None: print(f"\n elapsed: {time.monotonic() - started:.0f}s") print("\n A winner here is a candidate, not a decision: confirm it against the full") print(" 12-cell grid and the Flux gate before believing it.") - return 0 + # Non-zero on a rejected value: the sweep did not measure what it was asked to. + return 1 if rejected else 0 if __name__ == "__main__": From 897a8656fc56367fc9d344c29cf176f446bc000a Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 22:07:49 +0200 Subject: [PATCH 22/30] bench(voice): measure turn-taking through a phone line MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Every number in the README came from studio-clean 16kHz TTS, which is the standing reason not to trust the endpointing values for real callers: both thresholds tuned in that document decide when speech has stopped, and a noise floor is what makes that judgement hard. degrade.py adds a noise bed (pink or white, levelled per scenario against its own speech) and the telephone band (300-3400Hz + G.711 mu-law, hand-rolled since audioop is gone in 3.13), applied in ScriptFeeder.stream in the order a real path applies: speech and echo, then the room, then the line. Noise runs through the pauses on purpose — noise that stops with the speaker tells the endpointer where the turn ended. 16 offline checks via --verify, and the codec costs 0.16ms of the 20ms frame budget. First run on deepgram-flux/provider against a clean control at matched concurrency: correctness holds up (27/27 -> 25/27, zero ghost turns at both 15dB and 5dB) but the latency tail doesot — dead air p95 1442 -> 2282ms with p50 eou->audio flat, which is Flux's end-of-turn confidence taking longer on a noisy signal. That makes eot_threshold=0.8, chosen on clean audio, an open question rather than a settled one. No markers or baseline for the axis yet: the leak axis earned its table only after a first run showed which failures recurred. --- benchmarks/voice/README.md | 125 +++++ benchmarks/voice/cli.py | 10 + benchmarks/voice/degrade.py | 507 ++++++++++++++++++ benchmarks/voice/harness.py | 51 +- .../server/test_voice_detector_choice.py | 99 ++++ python/tests/server/test_voice_ws.py | 25 +- python/timbal/server/voice.py | 85 ++- python/timbal/voice/turn_detection.py | 12 +- 8 files changed, 883 insertions(+), 31 deletions(-) create mode 100644 benchmarks/voice/degrade.py create mode 100644 python/tests/server/test_voice_detector_choice.py diff --git a/benchmarks/voice/README.md b/benchmarks/voice/README.md index d1ebf698..ed30b668 100644 --- a/benchmarks/voice/README.md +++ b/benchmarks/voice/README.md @@ -1157,6 +1157,131 @@ threshold plus starting the reply on the eager event would let the LLM work duri the window Flux spends confirming, which is dead air currently buying nothing but confidence. +### The suite had been grading the default configuration all along without noticing + +Every finding above is about a detector someone chose. The interesting question is +what happens to someone who chooses nothing, and the matrix already answered it — +the answer was just sitting in a column nobody read as a default. + +`timbal.server.voice` only overrode the detector for Flux, where `stt_is_flux` +forces `provider`. For every other STT, an unset `turn_detector` fell through to +`resolve_turn_detector(None)`, which is `HeuristicTurnDetector` — the one detector +that cannot hold. Nova and ElevenLabs commit each fragment of a paused utterance +separately, so a detector that cannot hold cannot put them back together, and the +`heuristic` column is where the pause family goes to die. Counting scenarios +carrying a `known_failure` marker, out of 39: + +| STT | `heuristic` | `lexical` | `local` | +| --- | --- | --- | --- | +| `deepgram-nova` | 15 broken | 12 | **7** | +| `elevenlabs` | 14 broken | **6** | 8 | + +Fifteen of 39 broken was the shipping default for Nova. It reads as 100% in +`baseline.json` only because every one of those failures is marked — the markers +made the default's cost invisible in exactly the metric we gate on. The nine +scenarios `local` fixes on Nova are all one shape: `coding_pause`, +`coding_double_pause`, `food_pause`, `food_trailing_preposition`, +`medical_filler_midway`, `medical_long_utterance`, `support_pause`, +`support_pause_short`, `support_trailing_conjunction`. + +Worse, the two code paths already disagreed. `_warm_voice_models` resolves +`"local"` when `voice_config` names no detector, so a server with no configuration +was loading Smart Turn, Namo and Silero at startup and then handing the session a +detector that used none of them. The cost was being paid and the benefit discarded. + +`select_turn_detector_spec` now makes the choice explicitly, by STT, and +`test_server_voice.py` pins it — including the pre-existing Flux rule, which had no +test at all. The fallback is `lexical` rather than `local` when `timbal[voice]` is +absent, because `local` without an audio EOU model returns the heuristic decision +verbatim (its punctuation fallback sits *behind* the audio branch at +`turn_detection.py`), so it would have bought nothing. + +Left open deliberately: on ElevenLabs, `lexical` is the better of the two by this +count, and the four scenarios `local` breaks there are all one family — +`banking_correction`, `banking_digits_pause`, `food_trailing_preposition`, +`medical_self_correction`. That is the same correction-and-digits family whose +merges ElevenLabs' 1.2s VAD window performs for us, which suggests Smart Turn +scores the audio complete and cuts the hold short *before* the provider's window +merges the correction. Two scenarios is too thin a margin to special-case a +provider on, and it trades against latency the marker count cannot see: `local` is +what arms the VAD endpointing fast path, and ElevenLabs already has the worst dead +air in the matrix. Worth measuring, not guessing. + +### Every number above came from a recording booth + +The standing caveat on this whole document was that the audio is studio-clean: TTS +at 16 kHz, no noise floor, full bandwidth, handed straight to the STT. That is what +makes runs reproducible, and it is also why none of the endpointing values here +could be called right for a real caller. Both of the thresholds tuned in this +document — ElevenLabs' `vad_silence_threshold_secs` and Flux's `eot_threshold` — +decide when speech has *stopped*, which is precisely the judgement a noise floor +makes harder. + +`degrade.py` adds the missing path, applied in `ScriptFeeder.stream` in the order a +real one applies: + + user speech (+ echo leak) -> + noise bed -> telephone band -> STT + +Two details are load-bearing. The noise runs continuously, *through the pauses*: +noise gated to the clips would be a cue rather than a distractor, telling the +endpointer exactly where the utterance ended, and would test something easier than +clean audio rather than harder. And it is levelled per scenario against that +scenario's own speech (`active_rms`, which ignores silence), so `snr=15` means the +same thing in a scenario that is 60% deliberate pause as in one that is +wall-to-wall talking. `snr` is therefore the acoustic SNR at the microphone, not +the ratio the STT receives — speech and noise lose different amounts to the +telephone band. + +`--verify` earned its keep immediately by failing a check that encoded a wrong +belief of mine: that pink noise would survive the phone band better than white. It +is the reverse. At matched broadband level pink puts most of its energy below +300 Hz, exactly where the codec's high-pass throws it away, so white delivers more +in-band energy and is the harsher of the two. Pink is still the default because +rooms are pink; `white` is there to stress the STT. + +Not modelled, and worth knowing before quoting any number from this axis: packet +loss and jitter — a dropped 20 ms frame mid-word is a different failure and +plausibly the more dangerous one for turn-taking — and accent, which is a TTS voice +axis rather than a DSP one. This is still English in one voice. + +First measurement, `deepgram-flux/provider`, the primary production cell, whole +suite. The clean row is a control run at the same concurrency, not the stored +baseline, because parallel runs distort latency and comparing against a serial +baseline would have attributed that distortion to the noise: + +| mic path | passed | ghost turns | dead air p50 | dead air p95 | eou→audio p95 | +| --- | --- | --- | --- | --- | --- | +| clean | 27/27 | 0 | 652ms | 1442ms | 312ms | +| `snr=15,phone` | 25/27 | 0 | 860ms | 2282ms | 690ms | +| `snr=5,phone` | 25/27 | 0 | 845ms | 2007ms | 465ms | + +The reassuring half: turn-taking degrades gracefully in *correctness*. No ghost +turns at either level, no session errors, and the failures are two scenarios rather +than a collapse — a 10 dB change in noise barely moves the pass rate, which says +the cliff is not nearby. + +The half that matters more: the cost shows up as latency, and it is large. Dead air +p50 rises ~200ms and p95 nearly doubles, while `eou→audio` p50 barely moves +(217 -> 223ms) and its p95 more than doubles. That shape — median flat, tail +blowing out — is Flux's end-of-turn confidence taking longer to clear a noisy +signal. Which lands directly on a decision made earlier in this document: +`eot_threshold=0.8` was chosen on clean audio, on the argument that +214ms of dead +air bought fourteen points of pause merges. A patient threshold is exactly the +setting whose cost noise inflates, so that trade needs re-measuring here before it +can be called right for real callers. Sweeping `eot_threshold` *under* `--mic-path` +is the obvious next move and is now a one-liner. + +`food_trailing_preposition` is the one scenario that fails under noise having +passed clean, at both levels. It is intermittent rather than deterministic — a +single repeat merged correctly — and the partials show the mechanism: Flux hears +"Can you deliver it to" as "Can you do", then emits a stray `--` marker mid-stream, +so the fragment it endpoints is not the fragment the scenario is about. + +Deliberately not done yet: no markers and no baseline for this axis. The leak axis +earned its marker table only after a first run showed which failures recurred, and +inventing one here before knowing whether a scenario fails at 15 dB, at 5 dB, or +only in parallel would be bookkeeping ahead of evidence. + ## Running ```bash diff --git a/benchmarks/voice/cli.py b/benchmarks/voice/cli.py index 4995b88d..efecb2ba 100644 --- a/benchmarks/voice/cli.py +++ b/benchmarks/voice/cli.py @@ -38,6 +38,7 @@ from dataclasses import dataclass import structlog +from degrade import parse_mic_path from dotenv import load_dotenv from harness import HarnessConfig, RunResult, coerce_param, config_rejection, run_scenario from scenario import SCENARIOS, Scenario, select @@ -152,6 +153,14 @@ async def main() -> int: "realistic imperfect echo canceller); exercises the echo suppressor, which clean " "user-only audio never does", ) + parser.add_argument( + "--mic-path", + metavar="SPEC", + help="degrade the mic path: comma-separated 'snr=' (noise floor, levelled " + "against this scenario's speech), 'pink'|'white', and 'phone' (300-3400Hz + " + "G.711). Every baseline in the repo was measured without this, on studio-clean " + "16kHz TTS; e.g. --mic-path snr=15,phone", + ) # Reproducing one cell of a sweep with the event stream visible was the missing # step between "this value scores worse" and knowing why. parser.add_argument( @@ -200,6 +209,7 @@ async def main() -> int: language=args.language, dump=args.dump, aec_leak=args.aec_leak, + mic_path=parse_mic_path(args.mic_path), stt_extra=stt_extra, detector_params=detector_params, ) diff --git a/benchmarks/voice/degrade.py b/benchmarks/voice/degrade.py new file mode 100644 index 00000000..3a9303a2 --- /dev/null +++ b/benchmarks/voice/degrade.py @@ -0,0 +1,507 @@ +"""Microphone-path degradation for the voice replay harness. + +Every number this suite has produced came from clean 16 kHz TTS speech handed +straight to the STT: no room noise, no telephone band, no companding. That makes +the measurements reproducible, and it is also the standing reason not to trust +them for real callers. Endpointing thresholds in particular are tuned against +synthetic prosody in silence — `vad_silence_threshold_secs` on ElevenLabs and +`eot_threshold` on Flux both decide when speech has *stopped*, which is precisely +the judgement a noise floor makes harder. + +This module builds the missing path, in the order a real one applies: + + user speech (+ echo leak) -> + noise bed -> telephone band -> STT + +Noise is continuous, including through silence. That matters more than the level: +noise that starts and stops with the speech is a *cue* — it tells the endpointer +exactly where the utterance ended — so gating it to the clips would test +something easier than clean audio rather than harder. + +Deliberately not modelled, and worth knowing before reading any result from here: +packet loss and jitter. A dropped 20 ms frame mid-word is a different failure from +a noisy one and is likely the more dangerous of the two for turn-taking. + +Everything is deterministic given a seed, because a degradation axis that cannot +be replayed cannot be bisected. + +Standalone use:: + + uv run python benchmarks/voice/degrade.py --verify + uv run python benchmarks/voice/degrade.py --wav 15 --telephone "some text" +""" + +from __future__ import annotations + +import argparse +import array +import asyncio +import math +import random +import sys +from dataclasses import dataclass +from pathlib import Path + +from synth import ( + BYTES_PER_SECOND, + FRAME_BYTES, + SAMPLE_RATE, + duration_secs, + synthesize_clips, + write_wav, +) + +# --------------------------------------------------------------------------- +# G.711 mu-law companding +# --------------------------------------------------------------------------- +# +# 8-bit logarithmic quantisation: ~38 dB SNR on speech, and coarse enough at low +# amplitude to matter for a VAD deciding whether near-silence is silence. + +_ULAW_BIAS = 0x84 +_ULAW_CLIP = 32635 +_ULAW_EXPONENT = [ + 0, 0, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, + *([4] * 16), *([5] * 32), *([6] * 64), *([7] * 128), +] + + +def _encode_ulaw(sample: int) -> int: + sign = 0x80 if sample < 0 else 0x00 + magnitude = min(-sample if sample < 0 else sample, _ULAW_CLIP) + _ULAW_BIAS + exponent = _ULAW_EXPONENT[(magnitude >> 7) & 0xFF] + mantissa = (magnitude >> (exponent + 3)) & 0x0F + return ~(sign | (exponent << 4) | mantissa) & 0xFF + + +def _decode_ulaw(byte: int) -> int: + byte = ~byte & 0xFF + magnitude = (((byte & 0x0F) << 3) + _ULAW_BIAS) << ((byte >> 4) & 0x07) + magnitude -= _ULAW_BIAS + return -magnitude if byte & 0x80 else magnitude + + +# One table lookup per sample beats two function calls: this runs on every frame +# of every run, inside the loop that also has to hit a 20ms deadline. +_COMPAND = [_decode_ulaw(_encode_ulaw(s)) for s in range(-32768, 32768)] + + +def compand(pcm: bytes) -> bytes: + """Round-trip PCM16 through G.711 mu-law, as a phone network would.""" + samples = array.array("h", pcm) + for i, s in enumerate(samples): + samples[i] = _COMPAND[s + 32768] + return samples.tobytes() + + +# --------------------------------------------------------------------------- +# Biquad filtering (RBJ cookbook, coefficients derived not tabulated) +# --------------------------------------------------------------------------- + +Coeffs = tuple[float, float, float, float, float] +BiquadState = list[float] + + +def _lowpass(fc: float, fs: int = SAMPLE_RATE, q: float = 0.7071) -> Coeffs: + w0 = 2 * math.pi * fc / fs + alpha = math.sin(w0) / (2 * q) + cos_w0 = math.cos(w0) + b0, b1, b2 = (1 - cos_w0) / 2, 1 - cos_w0, (1 - cos_w0) / 2 + a0, a1, a2 = 1 + alpha, -2 * cos_w0, 1 - alpha + return (b0 / a0, b1 / a0, b2 / a0, a1 / a0, a2 / a0) + + +def _highpass(fc: float, fs: int = SAMPLE_RATE, q: float = 0.7071) -> Coeffs: + w0 = 2 * math.pi * fc / fs + alpha = math.sin(w0) / (2 * q) + cos_w0 = math.cos(w0) + b0, b1, b2 = (1 + cos_w0) / 2, -(1 + cos_w0), (1 + cos_w0) / 2 + a0, a1, a2 = 1 + alpha, -2 * cos_w0, 1 - alpha + return (b0 / a0, b1 / a0, b2 / a0, a1 / a0, a2 / a0) + + +def new_state() -> BiquadState: + return [0.0, 0.0, 0.0, 0.0] + + +def _run_biquad(samples: list[float], c: Coeffs, state: BiquadState) -> None: + """In-place Direct Form I. ``state`` carries across calls. + + Filter state must survive frame boundaries: resetting per frame would stamp a + transient every 20ms, which is a periodic click the STT would hear and this + module would not be measuring. + """ + b0, b1, b2, a1, a2 = c + x1, x2, y1, y2 = state + for i, x0 in enumerate(samples): + y0 = b0 * x0 + b1 * x1 + b2 * x2 - a1 * y1 - a2 * y2 + samples[i] = y0 + x2, x1 = x1, x0 + y2, y1 = y1, y0 + state[0], state[1], state[2], state[3] = x1, x2, y1, y2 + + +# The G.711 passband. Two low-pass stages, because one 12 dB/octave skirt still +# leaks enough 5-6 kHz energy that the result sounds like a muffled wideband +# recording rather than a phone call. +_TELEPHONE_STAGES: tuple[Coeffs, ...] = ( + _highpass(300.0), + _lowpass(3400.0), + _lowpass(3400.0), +) + + +def telephone_state() -> list[BiquadState]: + return [new_state() for _ in _TELEPHONE_STAGES] + + +def band_limit(pcm: bytes, state: list[BiquadState] | None = None) -> bytes: + """Restrict to the 300-3400 Hz telephone band.""" + if state is None: + state = telephone_state() + samples = [float(s) for s in array.array("h", pcm)] + for stage, st in zip(_TELEPHONE_STAGES, state, strict=True): + _run_biquad(samples, stage, st) + out = array.array("h", bytes(len(pcm))) + for i, s in enumerate(samples): + out[i] = 32767 if s > 32767 else (-32768 if s < -32768 else int(s)) + return out.tobytes() + + +def resample_8k(pcm: bytes) -> bytes: + """Decimate to 8 kHz and interpolate back, as an 8 kHz link would. + + Only meaningful after :func:`band_limit`; on its own it would alias. The band + limit is what changes the sound, but the round trip is cheap and it is the + part that is literally true of a phone call. + """ + samples = array.array("h", pcm) + if not samples: + return pcm + out = array.array("h", bytes(len(pcm))) + for i in range(len(samples)): + if i % 2 == 0: + out[i] = samples[i] + else: + prev = samples[i - 1] + nxt = samples[i + 1] if i + 1 < len(samples) else prev + out[i] = (prev + nxt) // 2 + return out.tobytes() + + +# --------------------------------------------------------------------------- +# Noise +# --------------------------------------------------------------------------- + + +def rms(pcm: bytes) -> float: + samples = array.array("h", pcm) + if not samples: + return 0.0 + return math.sqrt(sum(float(s) * s for s in samples) / len(samples)) + + +def active_rms(pcm: bytes, floor_ratio: float = 0.1) -> float: + """RMS of the speech, ignoring the silence around and inside it. + + SNR has to be stated against the level of the speech, not the level of the + recording: a scenario that is 60% deliberate pause would otherwise get a much + louder noise bed than one that is not, and the two would stop being + comparable at the same nominal SNR. + """ + frame_rms = [rms(pcm[i : i + FRAME_BYTES]) for i in range(0, len(pcm), FRAME_BYTES)] + if not frame_rms: + return 0.0 + threshold = max(frame_rms) * floor_ratio + active = [r for r in frame_rms if r >= threshold] + if not active: + return 0.0 + return math.sqrt(sum(r * r for r in active) / len(active)) + + +def noise_rms_for_snr(speech_rms: float, snr_db: float) -> float: + return speech_rms / (10 ** (snr_db / 20)) + + +def white_noise(n: int, rng: random.Random) -> list[float]: + return [rng.gauss(0.0, 1.0) for _ in range(n)] + + +def pink_noise(n: int, rng: random.Random) -> list[float]: + """1/f noise (Kellet's economy method). + + Pink is the default because room, traffic and HVAC noise is pink, so it is the + honest stand-in for a caller who is not in a recording booth. + + Note it is not the harsher of the two in the telephone band: at matched + broadband level, pink puts most of its energy below 300 Hz where the codec's + high-pass removes it, so `white` delivers *more* in-band energy (measured in + ``--verify``). Use `white` to stress the STT, `pink` to be realistic. + """ + b = [0.0] * 7 + out: list[float] = [] + for _ in range(n): + w = rng.gauss(0.0, 1.0) + b[0] = 0.99886 * b[0] + w * 0.0555179 + b[1] = 0.99332 * b[1] + w * 0.0750759 + b[2] = 0.96900 * b[2] + w * 0.1538520 + b[3] = 0.86650 * b[3] + w * 0.3104856 + b[4] = 0.55000 * b[4] + w * 0.5329522 + b[5] = -0.7616 * b[5] - w * 0.0168980 + out.append(b[0] + b[1] + b[2] + b[3] + b[4] + b[5] + b[6] + w * 0.5362) + b[6] = w * 0.115926 + return out + + +NOISE_KINDS = ("pink", "white") + + +def noise_bed(secs: float, target_rms: float, *, kind: str = "pink", seed: int = 0) -> bytes: + """A loopable bed of noise at ``target_rms``, deterministic for ``seed``.""" + if kind not in NOISE_KINDS: + raise ValueError(f"unknown noise kind {kind!r}; expected one of {NOISE_KINDS}") + n = max(1, int(secs * SAMPLE_RATE)) + rng = random.Random(seed) + raw = pink_noise(n, rng) if kind == "pink" else white_noise(n, rng) + scale = 0.0 + current = math.sqrt(sum(s * s for s in raw) / len(raw)) + if current > 0: + scale = target_rms / current + out = array.array("h", bytes(n * 2)) + for i, s in enumerate(raw): + v = s * scale + out[i] = 32767 if v > 32767 else (-32768 if v < -32768 else int(v)) + return out.tobytes() + + +# --------------------------------------------------------------------------- +# The axis +# --------------------------------------------------------------------------- + +# One minute, looped. Long enough that no scenario hears a repeat, short enough +# that generating it costs a fraction of a second of the run's startup. +BED_SECS = 60.0 + + +@dataclass(frozen=True) +class MicPath: + """What happens to audio between the speaker's mouth and the STT. + + The default is the identity: every run before this axis existed. + """ + + snr_db: float | None = None + telephone: bool = False + noise: str = "pink" + seed: int = 0 + + @property + def active(self) -> bool: + return self.snr_db is not None or self.telephone + + @property + def label(self) -> str: + """Cell-label suffix, matching the `[leak=...]` axis convention.""" + parts = [] + if self.snr_db is not None: + kind = "" if self.noise == "pink" else f",{self.noise}" + parts.append(f"snr={self.snr_db:g}{kind}") + if self.telephone: + parts.append("phone") + return f"[{','.join(parts)}]" if parts else "" + + def bed(self, speech_rms: float) -> bytes: + """The noise to mix in, scaled against the measured speech level. + + Returned *clean*: the caller mixes it with the speech and then runs the + codec over the sum, which is the order a real microphone and line apply. + So ``snr_db`` is the acoustic SNR at the microphone, not the SNR the STT + receives — speech and noise lose different amounts of energy to the + telephone band, so the ratio downstream of it is not the same number. + """ + if self.snr_db is None or speech_rms <= 0: + return b"" + target = noise_rms_for_snr(speech_rms, self.snr_db) + return noise_bed(BED_SECS, target, kind=self.noise, seed=self.seed) + + def apply(self, pcm: bytes, state: list[BiquadState] | None = None) -> bytes: + """Run the codec over one frame or clip. Pass ``state`` to keep it continuous.""" + if not self.telephone: + return pcm + return compand(resample_8k(band_limit(pcm, state))) + + +def parse_mic_path(spec: str | None, *, seed: int = 0) -> MicPath: + """Parse ``--mic-path`` : comma-separated ``snr=15``, ``white``, ``phone``. + + Examples: ``snr=15``, ``phone``, ``snr=10,white,phone``. + """ + if not spec: + return MicPath(seed=seed) + snr_db: float | None = None + telephone = False + noise = "pink" + for token in (t.strip().lower() for t in spec.split(",") if t.strip()): + if token in ("phone", "telephone", "g711"): + telephone = True + elif token in NOISE_KINDS: + noise = token + elif token.startswith("snr="): + snr_db = float(token[4:]) + else: + raise ValueError( + f"unknown --mic-path token {token!r}; expected snr=, " + f"one of {NOISE_KINDS}, or 'phone'" + ) + return MicPath(snr_db=snr_db, telephone=telephone, noise=noise, seed=seed) + + +# --------------------------------------------------------------------------- +# CLI +# --------------------------------------------------------------------------- + + +def _tone(freq: float, secs: float, amplitude: int = 8000) -> bytes: + n = int(secs * SAMPLE_RATE) + out = array.array("h", bytes(n * 2)) + for i in range(n): + out[i] = int(amplitude * math.sin(2 * math.pi * freq * i / SAMPLE_RATE)) + return out.tobytes() + + +def _db(ratio: float) -> float: + return 20 * math.log10(ratio) if ratio > 0 else -math.inf + + +def _verify() -> int: + """Offline checks: no API key, no network.""" + checks: list[tuple[str, bool, str]] = [] + + # Companding must be idempotent, or repeated application in a chain would + # keep degrading and the axis would not mean one pass through a codec. + speech_like = _tone(220, 0.5, amplitude=12000) + once = compand(speech_like) + twice = compand(once) + checks.append(("compand is idempotent", once == twice, f"{len(once)} bytes")) + + err = rms(bytes(array.array("h", [a - b for a, b in + zip(array.array("h", speech_like), array.array("h", once), strict=True)]).tobytes())) + snr = _db(rms(speech_like) / err) if err else math.inf + checks.append(("compand SNR is G.711-like", 30 <= snr <= 45, f"{snr:.1f} dB")) + + # The band: 1kHz through, 6kHz gone, rumble gone. + for freq, lo, hi, name in ( + (1000.0, -2.0, 1.0, "1kHz passes"), + (6000.0, -math.inf, -25.0, "6kHz is rejected"), + (100.0, -math.inf, -12.0, "100Hz is rejected"), + ): + tone = _tone(freq, 0.5) + # Skip the filter's settling transient before measuring. + got = _db(rms(band_limit(tone)[FRAME_BYTES * 5 :]) / rms(tone[FRAME_BYTES * 5 :])) + checks.append((name, lo <= got <= hi, f"{got:+.1f} dB")) + + path = MicPath(snr_db=15.0, telephone=True) + checks.append(("telephone is deterministic", path.apply(speech_like) == path.apply(speech_like), "byte-exact")) + checks.append(("length is preserved", len(path.apply(speech_like)) == len(speech_like), f"{len(speech_like)} bytes")) + + # SNR must come out at the number that was asked for, or every result on this + # axis is labelled with a level it does not have. + speech = _tone(300, 1.0, amplitude=10000) + bytes(BYTES_PER_SECOND) # half speech, half silence + level = active_rms(speech) + checks.append(("active_rms ignores silence", abs(_db(level / rms(speech)) - 3.0) < 0.6, f"{_db(level / rms(speech)):+.1f} dB vs whole")) + bed = noise_bed(1.0, noise_rms_for_snr(level, 15.0), seed=1) + got_snr = _db(level / rms(bed)) + checks.append(("bed hits the requested SNR", abs(got_snr - 15.0) < 0.5, f"{got_snr:.2f} dB")) + + checks.append(("bed is deterministic", noise_bed(0.2, 500, seed=7) == noise_bed(0.2, 500, seed=7), "seed 7")) + checks.append(("seeds differ", noise_bed(0.2, 500, seed=7) != noise_bed(0.2, 500, seed=8), "7 vs 8")) + # What makes pink pink: energy rising towards DC. Checked below 300 Hz, which + # is also exactly the region the telephone high-pass throws away — so at + # matched broadband level, white ends up the harsher of the two in-band. + def _sub_300(pcm: bytes) -> float: + samples = [float(s) for s in array.array("h", pcm)] + state = new_state() + stage = _lowpass(300.0) + _run_biquad(samples, stage, state) + return math.sqrt(sum(s * s for s in samples) / len(samples)) + + pink_bed = noise_bed(1.0, 2000, kind="pink", seed=3) + white_bed = noise_bed(1.0, 2000, kind="white", seed=3) + checks.append(( + "pink is low-frequency weighted", + _sub_300(pink_bed) > _sub_300(white_bed) * 2, + f"{_sub_300(pink_bed):.0f} vs {_sub_300(white_bed):.0f} below 300Hz", + )) + checks.append(( + "so white is harsher in the phone band", + rms(band_limit(white_bed)) > rms(band_limit(pink_bed)), + f"{rms(band_limit(white_bed)):.0f} vs {rms(band_limit(pink_bed)):.0f} in band", + )) + + checks.append(("labels round-trip", parse_mic_path("snr=10,white,phone").label == "[snr=10,white,phone]", parse_mic_path("snr=10,white,phone").label)) + checks.append(("identity by default", not MicPath().active and MicPath().label == "", "no suffix")) + + # This runs inside the loop that must hand the session a frame every 20ms, so + # the cost is part of the contract, not an implementation detail. + frame = _tone(440, 0.02) + state = telephone_state() + import time + + t0 = time.perf_counter() + reps = 200 + for _ in range(reps): + MicPath(telephone=True).apply(frame, state) + per_frame_ms = (time.perf_counter() - t0) / reps * 1000 + checks.append(( + "cost fits the frame budget", + per_frame_ms < 4.0, + f"{per_frame_ms:.2f} ms per 20 ms frame ({per_frame_ms / 20 * 100:.0f}%)", + )) + + for name, ok, detail in checks: + print(f" {'ok ' if ok else 'FAIL'} {name:<44} {detail}") + failed = [name for name, ok, _ in checks if not ok] + print(f"\n{len(checks) - len(failed)}/{len(checks)} checks passed") + return 0 if not failed else 1 + + +async def _write_sample(text: str, spec: str, out: Path | None) -> int: + path = parse_mic_path(spec) + clips = await synthesize_clips([text]) + clean = clips[text] + bed = path.bed(active_rms(clean)) + # Same order as ScriptFeeder.stream, or this writes a file that sounds like + # something the harness never feeds: noise into the mic, then the line. + degraded = clean + if bed: + from harness import mix_pcm16 + + degraded = mix_pcm16(degraded, bed[: len(degraded)], 1.0) + degraded = path.apply(degraded) + out = out or Path(__file__).parent / "results" / "synth" / f"degraded{path.label}.wav" + write_wav(out, degraded) + print(f"{duration_secs(degraded):.2f}s {path.label or '[clean]'} -> {out}") + return 0 + + +def main() -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("text", nargs="*", help="text to synthesize and degrade") + parser.add_argument("--verify", action="store_true", help="offline self-checks") + parser.add_argument("--mic-path", default="snr=15,phone", help="e.g. 'snr=15,phone'") + parser.add_argument("-o", "--out", type=Path) + args = parser.parse_args() + + if args.verify: + return _verify() + if not args.text: + parser.print_help() + return 2 + + from dotenv import load_dotenv + + load_dotenv(override=True) + return asyncio.run(_write_sample(" ".join(args.text), args.mic_path, args.out)) + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/benchmarks/voice/harness.py b/benchmarks/voice/harness.py index 5782c2ad..e5ba0c29 100644 --- a/benchmarks/voice/harness.py +++ b/benchmarks/voice/harness.py @@ -28,6 +28,7 @@ from dataclasses import dataclass, field from typing import Any +from degrade import MicPath, active_rms, telephone_state from scenario import ( AwaitAssistantAudio, AwaitAssistantDone, @@ -98,10 +99,15 @@ class HarnessConfig: # Fraction of the assistant's own output mixed back into the mic, standing # in for imperfect echo cancellation. 0.0 is every run before this one. aec_leak: float = 0.0 + # Noise floor and telephone band between the speaker and the STT. The default + # is the identity — studio-clean 16kHz TTS, which is what every number in the + # README was measured on and the main reason to be careful quoting them for + # real callers. + mic_path: MicPath = field(default_factory=MicPath) @property def label(self) -> str: - suffix = "" + suffix = self.mic_path.label if self.aec_leak: suffix += f"[leak={self.aec_leak}]" for params in (self.detector_params, self.stt_extra): @@ -208,6 +214,12 @@ class ScriptFeeder: Every run before this fed clean user-only audio, which means ``_likely_stt_echo`` — the guard that stops the assistant interrupting itself on speaker bleed — had never once been exercised. + + ``mic_path`` adds a noise floor and the telephone band. It applies here, at the + last moment before the frame leaves, rather than to the clips: a real mic path + degrades *everything* it carries — the user, the silence between them, and the + echo — and the noise has to keep running through the pauses, since noise that + stops when the speaker does would tell the endpointer where the turn ended. """ # Cap on buffered assistant audio. TTS generates faster than realtime, so an @@ -216,12 +228,31 @@ class ScriptFeeder: # test than the thing being simulated. MAX_LEAK_SECS = 1.0 - def __init__(self, leak_gain: float = 0.0) -> None: + def __init__(self, leak_gain: float = 0.0, mic_path: MicPath | None = None) -> None: self._pending: deque[bytes] = deque() self._leak = bytearray() self._leak_gain = leak_gain self._max_leak_bytes = int(BYTES_PER_SECOND * self.MAX_LEAK_SECS) self._stopped = False + self._mic_path = mic_path or MicPath() + # One filter state for the whole session, so the codec has no per-frame + # transient, and one read position so the bed plays as continuous noise + # rather than restarting every 20ms. + self._codec_state = telephone_state() + self._bed = b"" + self._bed_pos = 0 + + def set_noise_bed(self, bed: bytes) -> None: + self._bed = bed + + def _next_noise(self) -> bytes | None: + if not self._bed: + return None + if self._bed_pos + FRAME_BYTES > len(self._bed): + self._bed_pos = 0 + frame = self._bed[self._bed_pos : self._bed_pos + FRAME_BYTES] + self._bed_pos += FRAME_BYTES + return frame def push(self, pcm: bytes) -> None: self._pending.extend(frames(pcm)) @@ -261,6 +292,12 @@ async def stream(self) -> AsyncIterator[bytes]: frame = self._pending.popleft() if self._pending else SILENCE_FRAME if (leak := self._next_leak()) is not None: frame = mix_pcm16(frame, leak, self._leak_gain) + # Speech and echo first, then the room, then the line: the noise is + # picked up by the microphone, so it goes through the codec too. + if (noise := self._next_noise()) is not None: + frame = mix_pcm16(frame, noise, 1.0) + if self._mic_path.telephone: + frame = self._mic_path.apply(frame, self._codec_state) yield frame next_at += FRAME_SECS await asyncio.sleep(max(0.0, next_at - time.monotonic())) @@ -428,7 +465,15 @@ async def run_scenario( record_audio=config.dump, ) - feeder = ScriptFeeder(leak_gain=config.aec_leak) + feeder = ScriptFeeder(leak_gain=config.aec_leak, mic_path=config.mic_path) + if config.mic_path.snr_db is not None: + # Level the noise against this scenario's own speech, so the same nominal + # SNR means the same thing in a scenario that is mostly pause as in one + # that is wall-to-wall talking. + spoken = b"".join( + clips[s.clip_key] for s in scenario.script if isinstance(s, Say) and s.clip_key in clips + ) + feeder.set_noise_bed(config.mic_path.bed(active_rms(spoken))) playback = PlaybackSim() assistant_speaking = asyncio.Event() # session.close() interrupts any reply still playing. That teardown interrupt diff --git a/python/tests/server/test_voice_detector_choice.py b/python/tests/server/test_voice_detector_choice.py new file mode 100644 index 00000000..043ee3ce --- /dev/null +++ b/python/tests/server/test_voice_detector_choice.py @@ -0,0 +1,99 @@ +"""Turn detector selection for served voice sessions. + +The rules live in :func:`timbal.server.voice.select_turn_detector_spec` rather +than in the websocket handler precisely so they can be pinned here: they decide +what every deployment that doesn't configure a detector actually runs. +""" + +from timbal.server.voice import select_turn_detector_spec +from timbal.voice.turn_detection import HeuristicTurnDetector, LocalAudioTurnDetector + + +class _FakeLocal: + """Stand-in for what ``resolve_turn_detector("local")`` returns.""" + + def __init__(self, audio_eou: object | None) -> None: + self.audio_eou = audio_eou + + +def _with_extra(monkeypatch, *, available: bool) -> None: + """Fake the presence of timbal[voice] via the resolver's degradation signal.""" + import timbal.voice.turn_detection as td + + monkeypatch.setattr( + td, + "resolve_turn_detector", + lambda _spec=None: _FakeLocal(object() if available else None), + ) + + +class TestFluxOwnsEndpointing: + def test_nothing_chosen_gets_provider(self): + assert select_turn_detector_spec(None, None, stt_is_flux=True) == "provider" + + def test_local_is_overridden(self): + assert select_turn_detector_spec("local", None, stt_is_flux=True) == "provider" + + def test_lexical_is_overridden(self): + assert select_turn_detector_spec("lexical", None, stt_is_flux=True) == "provider" + + def test_an_instance_is_overridden_too(self): + # Documents current behaviour: Flux wins even over an explicit instance + # from voice_config, which is why the override is logged. + assert select_turn_detector_spec(LocalAudioTurnDetector(), None, stt_is_flux=True) == "provider" + + def test_explicit_heuristic_is_respected(self): + assert select_turn_detector_spec("heuristic", None, stt_is_flux=True) == "heuristic" + + def test_explicit_raw_is_respected(self): + assert select_turn_detector_spec("raw", None, stt_is_flux=True) == "raw" + + +class TestSilenceEndpointingDefault: + """Nova / ElevenLabs / anything that commits on a silence timeout.""" + + def test_defaults_to_local_with_the_extra(self, monkeypatch): + _with_extra(monkeypatch, available=True) + assert select_turn_detector_spec(None, None, stt_is_flux=False) == "local" + + def test_falls_back_to_lexical_without_the_extra(self, monkeypatch): + # `local` without an audio EOU model returns the heuristic decision + # verbatim, so it would not hold; `lexical` does, with no extra deps. + _with_extra(monkeypatch, available=False) + assert select_turn_detector_spec(None, None, stt_is_flux=False) == "lexical" + + def test_never_defaults_to_the_holdless_heuristic(self, monkeypatch): + for available in (True, False): + _with_extra(monkeypatch, available=available) + assert select_turn_detector_spec(None, None, stt_is_flux=False) != "heuristic" + + def test_explicit_heuristic_is_still_honoured(self): + assert select_turn_detector_spec("heuristic", None, stt_is_flux=False) == "heuristic" + + def test_an_instance_is_passed_through(self): + detector = HeuristicTurnDetector() + assert select_turn_detector_spec(detector, None, stt_is_flux=False) is detector + + def test_a_factory_is_passed_through(self): + def factory() -> HeuristicTurnDetector: + return HeuristicTurnDetector() + + assert select_turn_detector_spec(factory, None, stt_is_flux=False) is factory + + +class TestClientOverride: + def test_client_mode_beats_the_server_spec(self): + assert select_turn_detector_spec("local", "heuristic", stt_is_flux=False) == "heuristic" + + def test_client_mode_beats_a_server_instance(self): + assert select_turn_detector_spec(LocalAudioTurnDetector(), "lexical", stt_is_flux=False) == "lexical" + + def test_blank_client_mode_is_ignored(self): + assert select_turn_detector_spec("lexical", " ", stt_is_flux=False) == "lexical" + + def test_non_string_client_spec_is_refused(self): + # A browser must not be able to hand the server a callable. + assert select_turn_detector_spec("lexical", {"mode": "local"}, stt_is_flux=False) == "lexical" + + def test_client_cannot_escape_the_flux_override(self): + assert select_turn_detector_spec(None, "local", stt_is_flux=True) == "provider" diff --git a/python/tests/server/test_voice_ws.py b/python/tests/server/test_voice_ws.py index c327710a..53dd526f 100644 --- a/python/tests/server/test_voice_ws.py +++ b/python/tests/server/test_voice_ws.py @@ -289,12 +289,14 @@ def test_session_started_advertises_playback_acks( app = create_app() with TestClient(app) as client: with client.websocket_connect("/voice/ws") as ws: - ws.send_json({}) + # Pinned, not defaulted: this asserts what a detector *without* an + # audio EOU advertises, so it must not follow the server default. + ws.send_json({"turn_detector": "heuristic"}) messages = _collect_ws_messages(ws) started = next(m for m in messages if m["type"] == "session_started") assert started["playback_acks"] == "recommended" - # Default heuristic detector has no audio EOU model → the local VAD + # The heuristic detector has no audio EOU model → the local VAD # endpointing fast path never arms, and session_started must say so. assert started["vad_endpointing"] is False @@ -530,13 +532,20 @@ def test_client_mode_overrides_server_default(self, monkeypatch, tmp_path: Path) ) assert started["turn_detector"] == "LexicalTurnDetector" - def test_default_is_heuristic_and_advertised(self, monkeypatch, tmp_path: Path) -> None: + # A holding detector: which one depends on whether timbal[voice] is installed + # (see test_voice_detector_choice.py, which pins that branch directly). The + # contract asserted here is that an unconfigured session gets a detector that + # *can* hold — the holdless heuristic splits paused utterances into several + # turns on any STT that endpoints on silence. + _HOLDS = ("LocalAudioTurnDetector", "LexicalTurnDetector") + + def test_default_holds_and_is_advertised(self, monkeypatch, tmp_path: Path) -> None: started = self._run_session(monkeypatch, tmp_path, {}) - assert started["turn_detector"] == "HeuristicTurnDetector" + assert started["turn_detector"] in self._HOLDS def test_non_string_client_value_is_ignored(self, monkeypatch, tmp_path: Path) -> None: started = self._run_session(monkeypatch, tmp_path, {"turn_detector": {"evil": True}}) - assert started["turn_detector"] == "HeuristicTurnDetector" + assert started["turn_detector"] in self._HOLDS def test_unknown_mode_name_falls_back_to_default(self, monkeypatch, tmp_path: Path) -> None: started = self._run_session(monkeypatch, tmp_path, {"turn_detector": "quantum"}) @@ -642,7 +651,11 @@ def test_audio_chunks_are_valid_base64_pcm( app = create_app() with TestClient(app) as client: with client.websocket_connect("/voice/ws") as ws: - ws.send_json({}) + # This is a transport test: it needs the injected commit to start a + # turn immediately. A holding detector (the server default) would + # correctly park unpunctuated "test" for seconds and produce no + # audio at all. + ws.send_json({"turn_detector": "heuristic"}) messages = _collect_ws_messages(ws) audio_msgs = [m for m in messages if m["type"] == "audio"] diff --git a/python/timbal/server/voice.py b/python/timbal/server/voice.py index 9df818e4..0a14c426 100644 --- a/python/timbal/server/voice.py +++ b/python/timbal/server/voice.py @@ -162,7 +162,8 @@ def _import_stack() -> None: elif isinstance(td, str) and td.strip().lower() in ("local", "audio", "smart_turn"): detector = resolve_turn_detector(td) elif td is None: - # Playground often switches to Smart Turn on first Start — warm it. + # "local" is the default for non-Flux STT (see the session setup), and + # the playground also switches to Smart Turn on first Start. detector = resolve_turn_detector("local") if isinstance(detector, LocalAudioTurnDetector): @@ -194,6 +195,60 @@ async def voice_page(request: Request) -> HTMLResponse: return HTMLResponse(html) +def select_turn_detector_spec(server_spec: Any, client_spec: Any, *, stt_is_flux: bool) -> Any: + """Choose the turn detector for a session: a mode name, instance, or factory. + + ``server_spec`` comes from ``runnable.voice_config`` and may be any of those + three. ``client_spec`` comes over the wire and is honoured only as a mode + name — a browser must not be able to inject a callable — but is otherwise + preferred, so the playground can A/B detectors. + + The choice is made here rather than in + :func:`~timbal.voice.turn_detection.resolve_turn_detector` because it turns + on the STT: whichever mode is best depends on how well the provider + endpoints, and only the session setup knows which provider is in play. + """ + spec = server_spec + if isinstance(client_spec, str) and client_spec.strip(): + spec = client_spec + elif client_spec is not None and not isinstance(client_spec, str): + logger.warning("voice_ws_bad_turn_detector", error="client turn_detector must be a mode name string") + + mode = spec.strip().lower() if isinstance(spec, str) else None + if stt_is_flux: + # Flux owns EOU (~260ms). Local/lexical run *after* EndOfTurn and add a + # second HOLD tax; they also disable the useful Provider path. Force + # provider unless the caller explicitly picked heuristic/raw/provider. + if mode is None or mode in ("local", "audio", "smart_turn", "lexical"): + if spec is not None: + # Includes an instance or factory from voice_config, which this + # overrides too — worth saying so rather than silently ignoring. + logger.info("voice_ws_flux_overrides_turn_detector", requested=str(spec), using="provider") + return "provider" + return spec + if spec is not None: + return spec + + # Nothing chosen. The holdless heuristic is the worst of the four on every + # backend that endpoints on silence — 65-69% against 96-100% for detectors + # that can hold — because Nova and ElevenLabs commit each fragment of a + # paused utterance separately, and only a hold puts them back together. + # + # The warmup path already resolved "local" for this case, so a server with no + # `turn_detector` configured was loading Smart Turn, Namo and Silero at + # startup and then handing the session a detector that used none of them. + # + # Without `timbal[voice]`, `local` returns the heuristic decision verbatim + # (its punctuation fallback sits behind the audio-EOU branch), so it would buy + # nothing; `lexical` holds an unfinished transcript with no extra deps. Asking + # the resolver beats probing imports: the degradation rule stays in one place. + from ..voice.turn_detection import resolve_turn_detector + + mode = "local" if getattr(resolve_turn_detector("local"), "audio_eou", None) is not None else "lexical" + logger.info("voice_ws_default_turn_detector", using=mode) + return mode + + @router.websocket("/ws") async def voice_ws(ws: WebSocket) -> None: from ..core.agent import Agent @@ -318,29 +373,17 @@ async def voice_ws(ws: WebSocket) -> None: # a mode name ("heuristic"|"provider"|"local"|"lexical"). The client JSON # may additionally select a *mode name* (string only — useful for A/B # testing detectors from the playground); instances and factories can never - # come over the wire. + # come over the wire. When neither picks one, the server chooses by STT + # rather than taking ``resolve_turn_detector``'s zero-dep default, because + # only here is the STT's endpointing behaviour known. from ..voice.turn_detection import resolve_turn_detector turn_detector = None - raw_td = defaults.get("turn_detector") - client_td = config.get("turn_detector") - if isinstance(client_td, str) and client_td.strip(): - raw_td = client_td - elif client_td is not None and not isinstance(client_td, str): - logger.warning("voice_ws_bad_turn_detector", error="client turn_detector must be a mode name string") - if stt_is_flux: - # Flux owns EOU (~260ms). Local/lexical run *after* EndOfTurn and add - # a second HOLD tax; they also disable the useful Provider path. Force - # provider unless the client explicitly picked heuristic/raw/provider. - td_mode = raw_td.strip().lower() if isinstance(raw_td, str) else None - if td_mode is None or td_mode in ("local", "audio", "smart_turn", "lexical"): - if td_mode is not None: - logger.info( - "voice_ws_flux_overrides_turn_detector", - requested=raw_td, - using="provider", - ) - raw_td = "provider" + raw_td = select_turn_detector_spec( + defaults.get("turn_detector"), + config.get("turn_detector"), + stt_is_flux=stt_is_flux, + ) if raw_td is not None: try: # voice_config is process-wide; VoiceSession clones the resolved diff --git a/python/timbal/voice/turn_detection.py b/python/timbal/voice/turn_detection.py index 6e1fa01c..68e633a8 100644 --- a/python/timbal/voice/turn_detection.py +++ b/python/timbal/voice/turn_detection.py @@ -13,11 +13,21 @@ **Modes** (see :func:`resolve_turn_detector`): -* ``heuristic`` (default) — :class:`HeuristicTurnDetector`, no extra deps +* ``heuristic`` (resolver default) — :class:`HeuristicTurnDetector`, no extra deps * ``provider`` — :class:`ProviderTurnDetector`, trust STT/realtime endpointing * ``local`` — :class:`LocalAudioTurnDetector` + injectable :class:`AudioEouModel` * ``lexical`` — :class:`LexicalTurnDetector`, optional zero-dep text overlay +``heuristic`` is the resolver's default only because it is the one mode that +needs no extras and makes no assumption about the STT. It is *not* the best +choice: it cannot hold, so on any STT that endpoints on silence it splits a +paused utterance into several turns (``benchmarks/voice`` measures 65-69% on +Nova and ElevenLabs against 96-100% for the holding modes). Pick by STT — +``provider`` for Deepgram Flux, ``local`` (or ``lexical`` without the +``timbal[voice]`` extra) for everything else. :mod:`timbal.server.voice` does +this for you; direct :class:`~timbal.voice.session.VoiceSession` users should +pass ``turn_detector=`` explicitly. + Provider-native paths (OpenAI ``semantic_vad``, ElevenLabs Scribe VAD commits, Deepgram Flux, Gemini Live) map to ``provider`` or a future realtime session that skips local detection entirely. We deliberately do **not** chase From 6c14d194ea1d797a8a26db0b387643da1f3966c2 Mon Sep 17 00:00:00 2001 From: berges99 Date: Mon, 27 Jul 2026 22:46:09 +0200 Subject: [PATCH 23/30] fix(voice): end hung calls instead of leaving the caller in silence MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Two ways a session could go quiet forever, closed: - A hung LLM, tool, or TTS drain now hits a per-turn wall-clock deadline (60s default, turn_timeout_secs in voice_config, <=0 disables). On expiry the session emits SessionError, speaks a short apology if nothing has played yet, and stays open for the next turn. The apology is bounded too — when the TTS is the hung component, an unbounded rescue would hang exactly like the turn it rescues. - A dead STT socket already ends the call, but only because the receive loop enqueues its end-of-stream sentinel on every exit path; drop it and the caller keeps talking to a session that can no longer hear. New tests pin the sentinel for normal and abnormal closes, that only abnormal ones surface an error, and that audio pushed at a dead socket is dropped rather than raised. --- python/tests/server/test_voice_ws.py | 65 +++++++ .../voice/test_provider_connection_loss.py | 148 ++++++++++++++++ python/tests/voice/test_session.py | 162 ++++++++++++++++++ python/timbal/server/voice.py | 10 ++ python/timbal/voice/session.py | 98 +++++++++-- 5 files changed, 472 insertions(+), 11 deletions(-) create mode 100644 python/tests/voice/test_provider_connection_loss.py diff --git a/python/tests/server/test_voice_ws.py b/python/tests/server/test_voice_ws.py index 53dd526f..44b548b3 100644 --- a/python/tests/server/test_voice_ws.py +++ b/python/tests/server/test_voice_ws.py @@ -625,6 +625,71 @@ def test_malformed_early_frames_do_not_end_handshake( assert started["turn_detector"] == "ProviderTurnDetector" +class TestVoiceWsTurnTimeoutConfig: + """``turn_timeout_secs`` / ``turn_timeout_fallback`` must reach the session.""" + + def _capture_session_kwargs(self, monkeypatch: pytest.MonkeyPatch) -> dict: + import timbal.voice as voice_pkg + + real = voice_pkg.VoiceSession + captured: dict = {} + + class _CapturingSession(real): # type: ignore[misc, valid-type] + def __init__(self, *args, **kwargs): + captured.update(kwargs) + super().__init__(*args, **kwargs) + + monkeypatch.setattr(voice_pkg, "VoiceSession", _CapturingSession, raising=False) + return captured + + def test_turn_timeout_keys_are_plumbed_into_the_session( + self, + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, + ) -> None: + spec = _write_agent_module(tmp_path) + monkeypatch.setenv("TIMBAL_RUNNABLE", spec) + for k in VOICE_ENV_KEYS: + monkeypatch.delenv(k, raising=False) + + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsRealtimeSTT", _make_stt_class([])) + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsStreamTTS", _make_tts_class()) + captured = self._capture_session_kwargs(monkeypatch) + + app = create_app() + with TestClient(app) as client: + with client.websocket_connect("/voice/ws") as ws: + ws.send_json({"turn_timeout_secs": 12, "turn_timeout_fallback": "hold on"}) + _collect_ws_messages(ws) + + assert captured["turn_timeout_secs"] == 12.0 + assert captured["turn_timeout_fallback"] == "hold on" + + def test_bad_turn_timeout_value_keeps_the_session_default( + self, + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, + ) -> None: + """A non-numeric value must be dropped, not zero the watchdog out.""" + spec = _write_agent_module(tmp_path) + monkeypatch.setenv("TIMBAL_RUNNABLE", spec) + for k in VOICE_ENV_KEYS: + monkeypatch.delenv(k, raising=False) + + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsRealtimeSTT", _make_stt_class([])) + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsStreamTTS", _make_tts_class()) + captured = self._capture_session_kwargs(monkeypatch) + + app = create_app() + with TestClient(app) as client: + with client.websocket_connect("/voice/ws") as ws: + ws.send_json({"turn_timeout_secs": "soon"}) + messages = _collect_ws_messages(ws) + + assert "turn_timeout_secs" not in captured + assert any(m["type"] == "session_started" for m in messages) + + class TestVoiceWsAudioTransport: """Verify audio bytes survive the base64 round-trip over WS.""" diff --git a/python/tests/voice/test_provider_connection_loss.py b/python/tests/voice/test_provider_connection_loss.py new file mode 100644 index 00000000..a2e9be2f --- /dev/null +++ b/python/tests/voice/test_provider_connection_loss.py @@ -0,0 +1,148 @@ +"""What happens to a call when a provider socket dies mid-conversation. + +There is no reconnection in the Deepgram adapter, so a dropped socket ends the +call. That is a deliberate-enough outcome, but it rests entirely on one +guarantee: the receive loop must enqueue its end-of-stream sentinel on *every* +exit path. ``VoiceSession._process_stt_events`` closes the session when +``stt.events()`` completes, and nothing else notices a dead STT — there is no +heartbeat and no "connected but silent" watchdog. Drop the sentinel and the +failure mode changes from "the call ends" to "the caller keeps talking to a +session that can no longer hear them, indefinitely, with no error". + +These tests pin that sentinel, for the normal-close case as well as the abnormal +one, because the normal case is the one that emits no error and so leaves no +other trace. +""" + +from __future__ import annotations + +import asyncio +from typing import Any + +import pytest +from timbal.voice.deepgram import _DeepgramSTTBase +from websockets.exceptions import ConnectionClosedError, ConnectionClosedOK +from websockets.frames import Close + + +class _ClosingWs: + """A socket that yields nothing and reports itself closed on first read.""" + + def __init__(self, error: BaseException) -> None: + self._error = error + self.sent: list[Any] = [] + + def __aiter__(self) -> _ClosingWs: + return self + + async def __anext__(self) -> str: + raise self._error + + async def send(self, _data: Any) -> None: + # Real sockets raise here too once closed; the adapter swallows it. + raise self._error + + +class _StubSTT(_DeepgramSTTBase): + """Concrete subclass: the base leaves ``_handle_message`` abstract.""" + + def _build_uri(self, _config: Any) -> str: + return "wss://example.invalid/listen" + + async def _handle_message(self, _msg: dict[str, Any]) -> None: + return None + + async def commit(self) -> None: + return None + + +def _stt(error: BaseException) -> _StubSTT: + stt = _StubSTT(api_key="test-key") + stt._ws = _ClosingWs(error) + return stt + + +NORMAL_CLOSES = ( + pytest.param(ConnectionClosedOK(Close(1000, ""), None), id="1000-normal"), + pytest.param(ConnectionClosedOK(Close(1001, "going away"), None), id="1001-going-away"), +) +ABNORMAL_CLOSES = ( + pytest.param(ConnectionClosedError(Close(1011, "internal error"), None), id="1011-internal"), + pytest.param(ConnectionClosedError(Close(1006, "abnormal"), None), id="1006-abnormal"), +) + + +class TestSttStreamAlwaysTerminates: + """``events()`` must complete when the socket dies, whatever the close code.""" + + @pytest.mark.parametrize("error", [*NORMAL_CLOSES, *ABNORMAL_CLOSES]) + async def test_receive_loop_enqueues_the_sentinel(self, error: BaseException) -> None: + stt = _stt(error) + await stt._receive_loop() + + drained = _drain_queue(stt) + missing = ( + f"no end-of-stream sentinel after {type(error).__name__}: events() would await " + f"forever and the session would run on with a dead STT (queued: {drained})" + ) + assert drained and drained[-1] is None, missing + + @pytest.mark.parametrize("error", [*NORMAL_CLOSES, *ABNORMAL_CLOSES]) + async def test_events_completes_rather_than_hanging(self, error: BaseException) -> None: + stt = _stt(error) + receiver = asyncio.create_task(stt._receive_loop()) + + async def _drain() -> list[str]: + texts = [] + with pytest.raises(RuntimeError) if _is_abnormal(error) else _no_raise(): + async for event in stt.events(): + texts.append(event.text) + return texts + + # A hang here is the bug this file exists to catch, so bound the wait. + await asyncio.wait_for(_drain(), timeout=2.0) + await asyncio.wait_for(receiver, timeout=2.0) + + async def test_abnormal_close_is_reported_and_normal_close_is_not(self) -> None: + """Only an abnormal code produces an error event. + + The consequence is worth stating plainly: on a 1000/1001 close mid-call the + session simply ends, indistinguishable from the user hanging up, and the + only trace is a debug-level ``dg_stt_ws_closed``. + """ + abnormal = _stt(ConnectionClosedError(Close(1011, "internal error"), None)) + await abnormal._receive_loop() + assert [e for e in _drain_queue(abnormal) if e is not None and e.type == "error"] + + normal = _stt(ConnectionClosedOK(Close(1000, ""), None)) + await normal._receive_loop() + assert [e for e in _drain_queue(normal) if e is not None] == [] + + async def test_push_audio_survives_a_dead_socket(self) -> None: + """Audio written to a closed socket must not raise into the audio task. + + It is silently dropped, which is only acceptable because the receive loop's + sentinel is already tearing the session down. + """ + stt = _stt(ConnectionClosedOK(Close(1000, ""), None)) + await stt.push_audio(b"\x00\x01" * 4096) + await stt._flush_audio() + + +class _no_raise: + def __enter__(self) -> None: + return None + + def __exit__(self, *exc: object) -> bool: + return False + + +def _is_abnormal(error: BaseException) -> bool: + return isinstance(error, ConnectionClosedError) and error.rcvd is not None and error.rcvd.code not in (1000, 1001) + + +def _drain_queue(stt: _StubSTT) -> list[Any]: + out = [] + while not stt._queue.empty(): + out.append(stt._queue.get_nowait()) + return out diff --git a/python/tests/voice/test_session.py b/python/tests/voice/test_session.py index 79a7204c..891224dc 100644 --- a/python/tests/voice/test_session.py +++ b/python/tests/voice/test_session.py @@ -535,6 +535,168 @@ async def test_stt_error_event_becomes_session_error(self) -> None: assert "STT" in errors[0].message +# --------------------------------------------------------------------------- +# Tests: agent-turn timeout +# --------------------------------------------------------------------------- + + +class _HungAgent: + """Duck-typed agent whose event stream never yields — models a hung LLM.""" + + def __call__(self, **_kwargs: object) -> AsyncIterator[object]: + return self._gen() + + async def _gen(self) -> AsyncIterator[object]: + await asyncio.Event().wait() + if False: # pragma: no cover — keep this an async generator + yield None + + +class _HungTTS(TextToSpeech): + """TTS whose synthesize never yields — models a hung synthesis provider.""" + + def __init__(self) -> None: + self.synthesize_calls: list[str] = [] + + async def connect(self, config: AudioOutputConfig) -> None: + pass + + async def synthesize(self, text: str) -> AsyncIterator[bytes]: + self.synthesize_calls.append(text) + await asyncio.Event().wait() + if False: # pragma: no cover — keep this an async generator + yield b"" + + async def close(self) -> None: + pass + + +class TestTurnTimeout: + async def test_hung_agent_times_out_speaks_fallback_and_stays_open(self) -> None: + """A silent hung turn must not leave the caller waiting forever. + + Expect: SessionError, spoken fallback, session accepts a second turn. + """ + stt = DelayedMockSTT() + tts = MockTTS() + session = VoiceSession( + agent=_HungAgent(), # type: ignore[arg-type] + stt=stt, + tts=tts, + turn_timeout_secs=0.15, + turn_timeout_fallback="Sorry, try again.", + ) + # Swap in a real agent for the *second* turn after the timeout. + live_agent = Agent(name="t", model=TestModel(responses=["Recovered."]), tools=[]) + + events: list[VoiceSessionEvent] = [] + + async def _empty_audio() -> AsyncIterator[bytes]: + return + yield # noqa: RET504 + + async def _drive() -> None: + while not any(isinstance(e, SessionStarted) for e in events): + await asyncio.sleep(0.01) + + await stt.inject(TranscriptEvent(type="committed", text="Are you there?")) + while not any(isinstance(e, SessionError) and "timed out" in e.message for e in events): + await asyncio.sleep(0.01) + while not any(isinstance(e, AgentTextDone) for e in events): + await asyncio.sleep(0.01) + + session.agent = live_agent + await stt.inject(TranscriptEvent(type="committed", text="Hello again")) + while sum(1 for e in events if isinstance(e, AgentTextDone)) < 2: + await asyncio.sleep(0.01) + await stt.finish() + + async def _run() -> None: + async with aclosing(session.run(_empty_audio())) as stream: + driver = asyncio.create_task(_drive()) + async for ev in stream: + events.append(ev) + await driver + + await asyncio.wait_for(_run(), timeout=5) + + errors = [e for e in events if isinstance(e, SessionError)] + assert any("timed out" in e.message for e in errors) + assert "Sorry, try again." in tts.synthesized_texts + assert any(isinstance(e, AgentTextDone) and e.text == "Sorry, try again." for e in events) + assert session.transcript[-1].role == "assistant" + assert "Recovered" in session.transcript[-1].text + + async def test_hung_tts_cannot_hang_the_timeout_rescue(self) -> None: + """When the TTS is the hung component, the fallback speak is bounded too. + + An unbounded rescue would hang exactly like the turn it rescues: agent + times out, the apology goes to the same dead TTS, and the caller waits + forever anyway. Expect: rescue attempted, given up, session closable. + """ + stt = DelayedMockSTT() + tts = _HungTTS() + session = VoiceSession( + agent=_HungAgent(), # type: ignore[arg-type] + stt=stt, + tts=tts, + turn_timeout_secs=0.15, + ) + events: list[VoiceSessionEvent] = [] + + async def _empty_audio() -> AsyncIterator[bytes]: + return + yield # noqa: RET504 + + async def _drive() -> None: + while not any(isinstance(e, SessionStarted) for e in events): + await asyncio.sleep(0.01) + await stt.inject(TranscriptEvent(type="committed", text="Hello?")) + while not any(isinstance(e, SessionError) for e in events): + await asyncio.sleep(0.01) + # The bounded rescue expires after min(turn_timeout_secs, 10s). + while not tts.synthesize_calls: + await asyncio.sleep(0.01) + await asyncio.sleep(0.3) + await stt.finish() + + async def _run() -> None: + async with aclosing(session.run(_empty_audio())) as stream: + driver = asyncio.create_task(_drive()) + async for ev in stream: + events.append(ev) + await driver + + await asyncio.wait_for(_run(), timeout=5) + + assert any(isinstance(e, SessionError) and "timed out" in e.message for e in events) + assert tts.synthesize_calls # rescue was attempted against the dead TTS + assert not any(isinstance(e, AgentTextDone) for e in events) # and abandoned + assert not session.transcript or session.transcript[-1].role != "assistant" + + async def test_timeout_disabled_when_secs_non_positive(self) -> None: + """``turn_timeout_secs <= 0`` must not arm a deadline.""" + session, _, _ = _make_session( + stt_script=[TranscriptEvent(type="committed", text="Hi")], + responses=["Hello!"], + ) + session.turn_timeout_secs = 0 + events = await _collect_events(session) + assert not any(isinstance(e, SessionError) for e in events) + assert any(isinstance(e, AgentTextDone) for e in events) + + async def test_fast_turn_unaffected_by_default_timeout(self) -> None: + session, _, tts = _make_session( + stt_script=[TranscriptEvent(type="committed", text="Hi")], + responses=["Hello!"], + ) + assert session.turn_timeout_secs > 0 + events = await _collect_events(session) + assert not any(isinstance(e, SessionError) for e in events) + assert any(isinstance(e, AgentTextDone) for e in events) + assert tts.synthesized_texts # real reply, not the timeout fallback + + # --------------------------------------------------------------------------- # Tests: _strip_markdown # --------------------------------------------------------------------------- diff --git a/python/timbal/server/voice.py b/python/timbal/server/voice.py index 0a14c426..edca0ae3 100644 --- a/python/timbal/server/voice.py +++ b/python/timbal/server/voice.py @@ -428,6 +428,15 @@ async def voice_ws(ws: WebSocket) -> None: # TODO(tool-filler): read a server-side `filler_phrases` voice_config key # (list of phrases or `(tool_name) -> str | None` callable) and pass it to # `VoiceSession(filler=...)` once tool-call filler speech returns. + session_kwargs: dict[str, Any] = {} + if "turn_timeout_secs" in merged: + try: + session_kwargs["turn_timeout_secs"] = float(merged["turn_timeout_secs"]) + except (TypeError, ValueError): + logger.warning("voice_ws_bad_turn_timeout_secs", value=repr(merged.get("turn_timeout_secs"))) + if "turn_timeout_fallback" in merged: + fb = merged["turn_timeout_fallback"] + session_kwargs["turn_timeout_fallback"] = None if fb is None else str(fb) session = VoiceSession( agent=runnable, stt=stt, @@ -437,6 +446,7 @@ async def voice_ws(ws: WebSocket) -> None: turn_detector=turn_detector, vad_endpointing=vad_endpointing, model=model_override, + **session_kwargs, ) async def _recv_loop() -> None: diff --git a/python/timbal/voice/session.py b/python/timbal/voice/session.py index 2d289797..f9ec72f7 100644 --- a/python/timbal/voice/session.py +++ b/python/timbal/voice/session.py @@ -53,6 +53,13 @@ logger = structlog.get_logger("timbal.voice.session") +# Wall-clock cap on a single agent turn (LLM stream + in-turn TTS drains). +# Without this a hung provider leaves the caller in silence forever. +DEFAULT_TURN_TIMEOUT_SECS = 60.0 +# Spoken when the turn times out before any audio was produced. Empty / None +# disables the apology; the session stays open either way. +DEFAULT_TURN_TIMEOUT_FALLBACK = "Sorry, I lost that for a moment. Could you say that again?" + async def _no_audio_score() -> float | None: """Audio-EOU scorer for detectors that have none — always abstains. @@ -375,6 +382,13 @@ class VoiceSession: Background tasks spawned via ``run_in_background`` are **not** cancelled; the agent decides their lifecycle. + Turn timeout + ------------ + Each agent turn is capped by ``turn_timeout_secs`` (default 60s). On + expiry the session emits :class:`SessionError`, speaks + ``turn_timeout_fallback`` when no audio has gone out yet, and stays open + for the next user turn. Set ``turn_timeout_secs <= 0`` to disable. + After the session closes, :attr:`transcript` contains the ordered list of committed user/assistant text, and (when ``record_audio=True``) :attr:`input_audio` / :attr:`output_audio` hold raw PCM bytes. @@ -392,6 +406,8 @@ def __init__( playback_tracker: PlaybackTracker | None = None, record_audio: bool = False, hold_timeout_secs: float = 1.5, + turn_timeout_secs: float = DEFAULT_TURN_TIMEOUT_SECS, + turn_timeout_fallback: str | None = DEFAULT_TURN_TIMEOUT_FALLBACK, vad_endpointing: bool | VadEndpointer | None = None, model: str | None = None, ): @@ -416,6 +432,12 @@ def __init__( # a per-decision override. Heuristic/provider never HOLD, so this is inert # unless an opt-in detector (local / lexical) is used. self.hold_timeout_secs = hold_timeout_secs + # Wall-clock cap for one agent turn. ``<= 0`` disables. On expiry the + # session emits SessionError, speaks ``turn_timeout_fallback`` if no + # audio has gone out yet, and stays open for the next user turn. + self.turn_timeout_secs = turn_timeout_secs + self.turn_timeout_fallback = turn_timeout_fallback + self._turn_deadline: float | None = None # VAD endpointing fast path (Silero speech-stop → audio EOU → stt.commit()). # None = auto: on when the detector exposes an audio EOU model and the # timbal[voice] extra is installed; False = off; True = on (warn when @@ -1536,10 +1558,28 @@ async def _handle_committed(self, text: str) -> None: # -- Internal: agent turn → TTS ---------------------------------------- + async def _await_turn_deadline(self, awaitable: Any) -> Any: + """Await ``awaitable``, raising :class:`TimeoutError` if the turn deadline elapses. + + ``turn_timeout_secs <= 0`` disables the deadline. Used for agent + ``__anext__`` and in-turn TTS drains so a hung LLM/tool cannot leave + the caller in silence indefinitely. + """ + deadline = self._turn_deadline + if deadline is None: + return await awaitable + remaining = deadline - time.monotonic() + if remaining <= 0: + raise TimeoutError("agent turn timed out") + return await asyncio.wait_for(awaitable, timeout=remaining) + async def _run_turn(self, user_text: str) -> None: self._is_speaking = True self._turn_assistant_text = "" self._turn_started_at = time.monotonic() + self._turn_deadline = ( + self._turn_started_at + self.turn_timeout_secs if self.turn_timeout_secs > 0 else None + ) self._turn_index += 1 self._turn_first_token_at = None self._turn_first_audio_at = None @@ -1571,6 +1611,7 @@ async def _run_turn(self, user_text: str) -> None: user_preview=user_text[:160], resume_from_saved_run_id=(self._last_run_context.id if self._last_run_context else None), saved_run_parent_id=(self._last_run_context.parent_id if self._last_run_context else None), + turn_timeout_secs=self.turn_timeout_secs, **_trace_debug_fields(), ) text_buffer = "" @@ -1582,7 +1623,21 @@ async def _run_turn(self, user_text: str) -> None: if self.model: agent_kwargs["model"] = self.model agen = self.agent(**agent_kwargs) - async for event in agen: + # Timed ``__anext__`` so a hung LLM/tool cannot stall forever. The + # for-body is unchanged; only the pull is deadline-aware. + while True: + try: + event = await self._await_turn_deadline(agen.__anext__()) + except StopAsyncIteration: + turn_phase = "agent_generator_exhausted" + logger.debug( + "turn_agent_loop_complete", + reason="generator_exhausted", + response_chars=len(full_response), + **_trace_debug_fields(), + ) + break + turn_phase = "awaiting_agent_event" if self._cancel_turn.is_set(): turn_phase = "cancel_turn_flag_at_iter_start" @@ -1737,21 +1792,13 @@ async def _run_turn(self, user_text: str) -> None: # so all PCM is queued before post-hook / trace save / finally. if not self._cancel_turn.is_set(): turn_phase = "await_tts_after_llm_output" - await self._await_tts_chain() + await self._await_turn_deadline(self._await_tts_chain()) # Attach provisional metrics: the outer Agent's trace is first # persisted in its generator ``finally``, before this turn's own # ``finally`` builds the final numbers. The finally re-saves the # trace with final metrics; this keeps the intermediate snapshot # meaningful if the process dies before then. self._attach_metrics_to_trace(self._build_turn_metrics(user_text, interrupted=False)) - else: - turn_phase = "agent_generator_exhausted" - logger.debug( - "turn_agent_loop_complete", - reason="generator_exhausted", - response_chars=len(full_response), - **_trace_debug_fields(), - ) # Normally stamped at the .llm OUTPUT event (before the TTS drain); # fall back here for runs that never produced one. @@ -1764,7 +1811,7 @@ async def _run_turn(self, user_text: str) -> None: if not self._cancel_turn.is_set(): turn_phase = "await_tts_before_done" - await self._await_tts_chain() + await self._await_turn_deadline(self._await_tts_chain()) turn_phase = "emit_agent_text_done" if full_response.strip(): self._transcript.append(TranscriptEntry(role="assistant", text=full_response)) @@ -1785,6 +1832,35 @@ async def _run_turn(self, user_text: str) -> None: ) turn_phase = f"cancelled_during_{turn_phase}" raise + except TimeoutError: + # Hung LLM / tool / TTS drain hit the wall-clock cap. Surface an + # error, speak a short apology if the caller heard nothing, and let + # the session stay open for a retry — do not re-raise. + turn_phase = "timeout" + logger.error( + "turn_timeout", + timeout_secs=self.turn_timeout_secs, + response_chars=len(full_response), + had_audio=self._turn_first_audio_at is not None, + **_trace_debug_fields(), + ) + await self._emit(SessionError(message=f"Turn timed out after {self.turn_timeout_secs:g}s")) + fallback = (self.turn_timeout_fallback or "").strip() + if fallback and self._turn_first_audio_at is None and not self._cancel_turn.is_set(): + try: + await self._abort_tts_stream() + # The hung component may be the TTS itself, in which case an + # unbounded rescue would hang exactly like the turn it is + # rescuing. Bound it; on expiry we give up on the apology. + await asyncio.wait_for( + self._speak(fallback), + timeout=min(self.turn_timeout_secs, 10.0), + ) + self._transcript.append(TranscriptEntry(role="assistant", text=fallback)) + await self._emit(AgentTextDone(text=fallback)) + self._turn_finalized_ok = True + except Exception as e: + logger.warning("turn_timeout_fallback_failed", error=str(e), exc_info=True) except Exception as e: turn_phase = "exception" logger.error("turn_error", error=str(e), exc_info=True) From 2a2b1169e8e258acd77413fd2e6964f958384491 Mon Sep 17 00:00:00 2001 From: berges99 Date: Tue, 28 Jul 2026 09:47:52 +0200 Subject: [PATCH 24/30] fix(voice): tell a provider hanging up apart from a user hanging up MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit A provider-initiated close with a normal code ended the session silently (Deepgram), while our own requested teardown could surface a spurious error (ElevenLabs). Both receive loops now gate on the _stop flag: requested closes are silent, unrequested ones — 1000/1001 included — surface an error before the end-of-stream sentinel. ElevenLabs audio sends also survive a dead socket now, instead of killing the periodic flusher and raising out of commit() into the VAD endpointing path. Dead-but-open TCP stays the websockets library's job (default ping keepalive, kept by both adapters) and flows through the same paths. The connection-loss suite runs the full matrix (2 providers x 4 close codes), and the hung-agent timeout test no longer races the retiring turn's finally block (1-in-5 flake, caught by the full-suite run). --- .../voice/test_provider_connection_loss.py | 150 ++++++++++-------- python/tests/voice/test_session.py | 7 + python/timbal/voice/deepgram.py | 12 +- python/timbal/voice/elevenlabs.py | 18 ++- 4 files changed, 118 insertions(+), 69 deletions(-) diff --git a/python/tests/voice/test_provider_connection_loss.py b/python/tests/voice/test_provider_connection_loss.py index a2e9be2f..dbc8393b 100644 --- a/python/tests/voice/test_provider_connection_loss.py +++ b/python/tests/voice/test_provider_connection_loss.py @@ -1,17 +1,25 @@ """What happens to a call when a provider socket dies mid-conversation. -There is no reconnection in the Deepgram adapter, so a dropped socket ends the -call. That is a deliberate-enough outcome, but it rests entirely on one -guarantee: the receive loop must enqueue its end-of-stream sentinel on *every* -exit path. ``VoiceSession._process_stt_events`` closes the session when -``stt.events()`` completes, and nothing else notices a dead STT — there is no -heartbeat and no "connected but silent" watchdog. Drop the sentinel and the -failure mode changes from "the call ends" to "the caller keeps talking to a -session that can no longer hear them, indefinitely, with no error". - -These tests pin that sentinel, for the normal-close case as well as the abnormal -one, because the normal case is the one that emits no error and so leaves no -other trace. +Neither STT adapter reconnects, so a dropped socket ends the call. Two +invariants make that ending honest instead of silent, and both are pinned here +for Deepgram and ElevenLabs alike: + +* The receive loop must enqueue its end-of-stream sentinel on *every* exit + path. ``VoiceSession._process_stt_events`` closes the session when + ``stt.events()`` completes, and nothing else notices a dead STT. Drop the + sentinel and the caller keeps talking to a session that can no longer hear + them, indefinitely, with no error. + +* An *unrequested* close — any code, 1000/1001 included — must surface an + error event. The provider hanging up mid-call is not the user hanging up; + before this was pinned, a normal-code close ended the session with a + debug-level log as its only trace. Requested closes (``close()`` sets + ``_stop`` before touching the socket) stay silent. + +A dead-but-open TCP connection is the websockets library's problem, not ours: +both adapters keep the library's default ping keepalive (20s interval, 20s +timeout), so a peer that stops answering pings surfaces in the receive loop as +``ConnectionClosedError`` 1011 and flows through the same paths pinned here. """ from __future__ import annotations @@ -21,12 +29,13 @@ import pytest from timbal.voice.deepgram import _DeepgramSTTBase +from timbal.voice.elevenlabs import ElevenLabsRealtimeSTT from websockets.exceptions import ConnectionClosedError, ConnectionClosedOK from websockets.frames import Close class _ClosingWs: - """A socket that yields nothing and reports itself closed on first read.""" + """A socket that yields nothing and reports itself closed on first use.""" def __init__(self, error: BaseException) -> None: self._error = error @@ -39,11 +48,11 @@ async def __anext__(self) -> str: raise self._error async def send(self, _data: Any) -> None: - # Real sockets raise here too once closed; the adapter swallows it. + # Real sockets raise here too once closed; the adapters swallow it. raise self._error -class _StubSTT(_DeepgramSTTBase): +class _StubDeepgramSTT(_DeepgramSTTBase): """Concrete subclass: the base leaves ``_handle_message`` abstract.""" def _build_uri(self, _config: Any) -> str: @@ -53,20 +62,29 @@ async def _handle_message(self, _msg: dict[str, Any]) -> None: return None async def commit(self) -> None: - return None + await self._flush_audio() + await self._send_json({"type": "Finalize"}) + + +def _deepgram(error: BaseException) -> _StubDeepgramSTT: + stt = _StubDeepgramSTT(api_key="test-key") + stt._ws = _ClosingWs(error) + return stt -def _stt(error: BaseException) -> _StubSTT: - stt = _StubSTT(api_key="test-key") +def _elevenlabs(error: BaseException) -> ElevenLabsRealtimeSTT: + stt = ElevenLabsRealtimeSTT(api_key="test-key") stt._ws = _ClosingWs(error) return stt -NORMAL_CLOSES = ( +PROVIDERS = ( + pytest.param(_deepgram, id="deepgram"), + pytest.param(_elevenlabs, id="elevenlabs"), +) +CLOSES = ( pytest.param(ConnectionClosedOK(Close(1000, ""), None), id="1000-normal"), pytest.param(ConnectionClosedOK(Close(1001, "going away"), None), id="1001-going-away"), -) -ABNORMAL_CLOSES = ( pytest.param(ConnectionClosedError(Close(1011, "internal error"), None), id="1011-internal"), pytest.param(ConnectionClosedError(Close(1006, "abnormal"), None), id="1006-abnormal"), ) @@ -75,9 +93,10 @@ def _stt(error: BaseException) -> _StubSTT: class TestSttStreamAlwaysTerminates: """``events()`` must complete when the socket dies, whatever the close code.""" - @pytest.mark.parametrize("error", [*NORMAL_CLOSES, *ABNORMAL_CLOSES]) - async def test_receive_loop_enqueues_the_sentinel(self, error: BaseException) -> None: - stt = _stt(error) + @pytest.mark.parametrize("make_stt", PROVIDERS) + @pytest.mark.parametrize("error", CLOSES) + async def test_receive_loop_enqueues_the_sentinel(self, make_stt, error: BaseException) -> None: + stt = make_stt(error) await stt._receive_loop() drained = _drain_queue(stt) @@ -87,61 +106,68 @@ async def test_receive_loop_enqueues_the_sentinel(self, error: BaseException) -> ) assert drained and drained[-1] is None, missing - @pytest.mark.parametrize("error", [*NORMAL_CLOSES, *ABNORMAL_CLOSES]) - async def test_events_completes_rather_than_hanging(self, error: BaseException) -> None: - stt = _stt(error) + @pytest.mark.parametrize("make_stt", PROVIDERS) + @pytest.mark.parametrize("error", CLOSES) + async def test_events_completes_and_raises_on_unrequested_close( + self, make_stt, error: BaseException + ) -> None: + """Every unrequested close — normal codes included — is an error, not a shrug.""" + stt = make_stt(error) receiver = asyncio.create_task(stt._receive_loop()) - async def _drain() -> list[str]: - texts = [] - with pytest.raises(RuntimeError) if _is_abnormal(error) else _no_raise(): - async for event in stt.events(): - texts.append(event.text) - return texts + async def _drain() -> None: + with pytest.raises(RuntimeError, match="STT connection closed"): + async for _ in stt.events(): + pass # A hang here is the bug this file exists to catch, so bound the wait. await asyncio.wait_for(_drain(), timeout=2.0) await asyncio.wait_for(receiver, timeout=2.0) - async def test_abnormal_close_is_reported_and_normal_close_is_not(self) -> None: - """Only an abnormal code produces an error event. - - The consequence is worth stating plainly: on a 1000/1001 close mid-call the - session simply ends, indistinguishable from the user hanging up, and the - only trace is a debug-level ``dg_stt_ws_closed``. - """ - abnormal = _stt(ConnectionClosedError(Close(1011, "internal error"), None)) - await abnormal._receive_loop() - assert [e for e in _drain_queue(abnormal) if e is not None and e.type == "error"] - normal = _stt(ConnectionClosedOK(Close(1000, ""), None)) - await normal._receive_loop() - assert [e for e in _drain_queue(normal) if e is not None] == [] +class TestRequestedCloseStaysSilent: + """Our own ``close()`` must not manufacture an error out of its side effects. - async def test_push_audio_survives_a_dead_socket(self) -> None: - """Audio written to a closed socket must not raise into the audio task. + ``close()`` sets ``_stop`` before touching the socket; the receive loop + reads that flag to tell a teardown we asked for apart from a provider + hanging up on us. An error event here races session close and can surface + a spurious SessionError on a perfectly normal hangup. + """ - It is silently dropped, which is only acceptable because the receive loop's - sentinel is already tearing the session down. - """ - stt = _stt(ConnectionClosedOK(Close(1000, ""), None)) - await stt.push_audio(b"\x00\x01" * 4096) - await stt._flush_audio() + @pytest.mark.parametrize("make_stt", PROVIDERS) + async def test_no_error_event_when_stop_was_requested(self, make_stt) -> None: + stt = make_stt(ConnectionClosedOK(Close(1000, ""), None)) + stt._stop.set() + await stt._receive_loop() + drained = _drain_queue(stt) + assert [e for e in drained if e is not None] == [] + assert drained[-1] is None # the sentinel still terminates events() -class _no_raise: - def __enter__(self) -> None: - return None +class TestSendsSurviveADeadSocket: + """Audio/control writes to a closed socket must not raise into their callers. - def __exit__(self, *exc: object) -> bool: - return False + Silent dropping is only acceptable because the receive loop's sentinel is + already tearing the session down. The callers that must not see a raise: + the session's audio forwarder (``push_audio``), the adapters' periodic + flushers, and the VAD endpointing fast path (``commit()``). + """ + @pytest.mark.parametrize("make_stt", PROVIDERS) + async def test_push_audio_and_flush(self, make_stt) -> None: + stt = make_stt(ConnectionClosedOK(Close(1000, ""), None)) + # Enough PCM to cross Deepgram's eager-send threshold (2560 bytes). + await stt.push_audio(b"\x00\x01" * 4096) + await stt._flush_audio() -def _is_abnormal(error: BaseException) -> bool: - return isinstance(error, ConnectionClosedError) and error.rcvd is not None and error.rcvd.code not in (1000, 1001) + @pytest.mark.parametrize("make_stt", PROVIDERS) + async def test_commit(self, make_stt) -> None: + stt = make_stt(ConnectionClosedOK(Close(1000, ""), None)) + await stt.push_audio(b"\x00\x01" * 64) + await stt.commit() -def _drain_queue(stt: _StubSTT) -> list[Any]: +def _drain_queue(stt: Any) -> list[Any]: out = [] while not stt._queue.empty(): out.append(stt._queue.get_nowait()) diff --git a/python/tests/voice/test_session.py b/python/tests/voice/test_session.py index 891224dc..c69a9b81 100644 --- a/python/tests/voice/test_session.py +++ b/python/tests/voice/test_session.py @@ -604,6 +604,13 @@ async def _drive() -> None: await asyncio.sleep(0.01) while not any(isinstance(e, AgentTextDone) for e in events): await asyncio.sleep(0.01) + # AgentTextDone is emitted while the turn's ``finally`` is still + # retiring it. A commit landing in that window sees an active + # assistant and gets dismissed as a trailing crumb of "Are you + # there?" — correct product behavior, wrong test timing. Wait for + # the turn task itself. + while session._current_turn_task is not None and not session._current_turn_task.done(): + await asyncio.sleep(0.01) session.agent = live_agent await stt.inject(TranscriptEvent(type="committed", text="Hello again")) diff --git a/python/timbal/voice/deepgram.py b/python/timbal/voice/deepgram.py index 7fd39cfe..c666afae 100644 --- a/python/timbal/voice/deepgram.py +++ b/python/timbal/voice/deepgram.py @@ -183,10 +183,14 @@ async def _receive_loop(self) -> None: continue await self._handle_message(msg) except ConnectionClosed as e: - logger.debug("dg_stt_ws_closed", error=str(e)) - # Deepgram closes normally after CloseStream; only surface abnormal - # closures as errors so the session tears down loudly. - if not self._stop.is_set() and e.rcvd is not None and e.rcvd.code not in (1000, 1001): + if self._stop.is_set(): + # Requested teardown (close() sent CloseStream); silence is correct. + logger.debug("dg_stt_ws_closed", error=str(e)) + else: + # Provider-initiated, any code — 1000/1001 included. The provider + # hanging up mid-call is not the user hanging up; ending the + # session silently made the two indistinguishable. + logger.warning("dg_stt_ws_closed_unrequested", error=str(e)) await self._queue.put(TranscriptEvent(type="error", text=f"STT connection closed: {e}")) except Exception as e: logger.error("dg_stt_receive_error", error=str(e), exc_info=True) diff --git a/python/timbal/voice/elevenlabs.py b/python/timbal/voice/elevenlabs.py index 7a58db3d..c1495dd9 100644 --- a/python/timbal/voice/elevenlabs.py +++ b/python/timbal/voice/elevenlabs.py @@ -166,7 +166,14 @@ async def _flush_audio(self, commit: bool = False) -> None: "commit": commit, "sample_rate": self._input_config.sample_rate if self._input_config else 16_000, } - await self._ws.send(json.dumps(msg)) + try: + await self._ws.send(json.dumps(msg)) + except ConnectionClosed: + # Dead socket: drop the audio. Acceptable only because the receive + # loop's sentinel is already tearing the session down — and required, + # because this path is called from the periodic flusher and from + # commit() (VAD endpointing), neither of which may raise. + pass async def _periodic_flush(self) -> None: try: @@ -208,8 +215,13 @@ async def _receive_loop(self) -> None: await self._queue.put(TranscriptEvent(type="error", text=f"STT fatal ({mt}): {err}")) break except ConnectionClosed as e: - logger.debug("el_stt_ws_closed", error=str(e)) - await self._queue.put(TranscriptEvent(type="error", text=f"STT connection closed: {e}")) + if self._stop.is_set(): + # Requested teardown; an error event here races session close and + # can surface a spurious SessionError on a normal hangup. + logger.debug("el_stt_ws_closed", error=str(e)) + else: + logger.warning("el_stt_ws_closed_unrequested", error=str(e)) + await self._queue.put(TranscriptEvent(type="error", text=f"STT connection closed: {e}")) except Exception as e: logger.error("el_stt_receive_error", error=str(e), exc_info=True) await self._queue.put(TranscriptEvent(type="error", text=f"STT receive error: {e}")) From c8e9a212fdd21eb074d91fe4f5306c1a0b645e0e Mon Sep 17 00:00:00 2001 From: berges99 Date: Tue, 28 Jul 2026 11:28:43 +0200 Subject: [PATCH 25/30] =?UTF-8?q?feat(voice):=20WebRTC=20transport=20?= =?UTF-8?q?=E2=80=94=20the=20server's=20clock=20becomes=20the=20played=20p?= =?UTF-8?q?osition?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit POST /voice/rtc (aiortc, WHIP-style offer/answer): mic and TTS ride Opus tracks, session events ride the client's data channel, and the downlink is paced server-side in 20ms frames — so barge-in truncation is exact from the transport's own clock, no playback acks, and the unspoken tail is dropped before it's ever sent. - voice/webrtc.py: PcmQueueTrack, PacedPlaybackTracker, track_to_pcm - server/voice.py: session build + event serialization extracted and shared with the WS handler (which now advertises transport: websocket) - server/rtc.py: signaling, pc lifecycle, 501 without aiortc (now part of timbal[voice]), TIMBAL_STUN_URL / TIMBAL_TURN_* for ICE - playground: transport dropdown; WebRTC forces browser noise suppression (RNNoise lives in the worklet and would be silently bypassed) - tests: pacing/played-axis units + a real aiortc loopback through the route --- pyproject.toml | 1 + python/tests/server/test_voice_rtc.py | 253 ++++++++++++++++++++++ python/tests/voice/test_webrtc.py | 157 ++++++++++++++ python/timbal/server/README.md | 36 ++- python/timbal/server/http.py | 2 + python/timbal/server/rtc.py | 212 ++++++++++++++++++ python/timbal/server/voice.html | 202 +++++++++++++++-- python/timbal/server/voice.py | 301 ++++++++++++++------------ python/timbal/voice/webrtc.py | 181 ++++++++++++++++ uv.lock | 149 +++++++++++++ 10 files changed, 1340 insertions(+), 154 deletions(-) create mode 100644 python/tests/server/test_voice_rtc.py create mode 100644 python/tests/voice/test_webrtc.py create mode 100644 python/timbal/server/rtc.py create mode 100644 python/timbal/voice/webrtc.py diff --git a/pyproject.toml b/pyproject.toml index aacc1e22..e1444a34 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -61,6 +61,7 @@ server = [ "websockets>=15.0.1", ] voice = [ + "aiortc>=1.9.0", "huggingface-hub>=0.28.0", "onnxruntime>=1.20.0", "transformers>=4.40.0", diff --git a/python/tests/server/test_voice_rtc.py b/python/tests/server/test_voice_rtc.py new file mode 100644 index 00000000..4f3cb93f --- /dev/null +++ b/python/tests/server/test_voice_rtc.py @@ -0,0 +1,253 @@ +"""End-to-end tests for ``POST /voice/rtc`` — a real aiortc loopback in one process. + +The test plays the browser: its own ``RTCPeerConnection``, a silent mic +track, and a client-created data channel, with SDP exchanged through the +actual FastAPI endpoint. Media and SCTP flow over localhost UDP between the +test's event loop and the TestClient portal loop. STT/TTS are mocked at the +module boundary exactly like ``test_voice_ws.py`` — everything from the +signaling down through ICE, DTLS, Opus, and the session is real. +""" + +# ruff: noqa: ARG002 +from __future__ import annotations + +import asyncio +import contextlib +import json +from pathlib import Path +from typing import Any + +import pytest + +pytest.importorskip("aiortc", reason="timbal[voice] extra (aiortc) not installed") + +from aiortc import RTCConfiguration, RTCPeerConnection, RTCSessionDescription # noqa: E402 +from aiortc.mediastreams import AudioStreamTrack # noqa: E402 +from fastapi.testclient import TestClient # noqa: E402 +from timbal.server.http import create_app # noqa: E402 +from timbal.voice.session import ( # noqa: E402 + AudioInputConfig, + SpeechToText, + TranscriptEvent, +) + +from .test_voice_ws import _make_tts_class, _write_agent_module # noqa: E402 +from .voice_env import VOICE_ENV_KEYS # noqa: E402 + + +def _make_delayed_stt_class(script: list[tuple[float, TranscriptEvent]], *, end_after: float = 1.0): + """An STT class replaying ``(delay_secs, event)`` pairs, then ending. + + The WS mocks replay instantly on connect; over RTC the session must + outlive the ICE/DTLS/SCTP handshake for anything to reach the client, so + events are spaced on a real clock. + """ + _script = list(script) + + class _STT(SpeechToText): + def __init__(self, api_key: Any = None) -> None: + self._queue: asyncio.Queue[TranscriptEvent | None] = asyncio.Queue() + self._feeder: asyncio.Task | None = None + + async def connect(self, config: AudioInputConfig) -> None: + async def _feed() -> None: + for delay, ev in _script: + await asyncio.sleep(delay) + await self._queue.put(ev) + await asyncio.sleep(end_after) + await self._queue.put(None) + + self._feeder = asyncio.create_task(_feed()) + + async def push_audio(self, chunk: bytes) -> None: + pass + + async def commit(self) -> None: + pass + + async def events(self): + while True: + item = await self._queue.get() + if item is None: + break + if item.text: + yield item + + async def close(self) -> None: + if self._feeder is not None and not self._feeder.done(): + self._feeder.cancel() + + return _STT + + +async def _rtc_call( + client: TestClient, + *, + config: dict | None = None, + timeout: float = 20.0, +) -> tuple[list[dict], list[Any]]: + """Run one full call as the browser would; returns (messages, downlink frames).""" + pc = RTCPeerConnection(configuration=RTCConfiguration(iceServers=[])) + pc.addTrack(AudioStreamTrack()) # silent mic + channel = pc.createDataChannel("events") + + messages: list[dict] = [] + frames: list[Any] = [] + ended = asyncio.Event() + + @channel.on("message") + def on_message(msg: Any) -> None: + data = json.loads(msg) + messages.append(data) + if data.get("type") == "session_ended": + ended.set() + + @pc.on("track") + def on_track(track: Any) -> None: + async def _pull() -> None: + with contextlib.suppress(Exception): + while True: + frames.append(await track.recv()) + + asyncio.ensure_future(_pull()) + + offer = await pc.createOffer() + await pc.setLocalDescription(offer) + resp = await asyncio.to_thread( + client.post, + "/voice/rtc", + json={"sdp": pc.localDescription.sdp, "type": "offer", "config": config or {}}, + ) + assert resp.status_code == 200, resp.text + await pc.setRemoteDescription(RTCSessionDescription(**resp.json())) + try: + await asyncio.wait_for(ended.wait(), timeout=timeout) + finally: + await pc.close() + return messages, frames + + +def _setup_env(monkeypatch: pytest.MonkeyPatch, tmp_path: Path, *, responses: list[str] | None = None) -> None: + spec = _write_agent_module(tmp_path, responses=responses) + monkeypatch.setenv("TIMBAL_RUNNABLE", spec) + for k in VOICE_ENV_KEYS: + monkeypatch.delenv(k, raising=False) + monkeypatch.setenv("TIMBAL_STUN_URL", "") # loopback: host candidates only + + +class TestVoiceRtcRoundTrip: + async def test_full_call_over_webrtc(self, monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: + _setup_env(monkeypatch, tmp_path, responses=["Hi there!"]) + monkeypatch.setattr( + "timbal.voice.elevenlabs.ElevenLabsRealtimeSTT", + _make_delayed_stt_class( + [(0.2, TranscriptEvent(type="committed", text="Hello"))], + end_after=1.5, + ), + ) + monkeypatch.setattr( + "timbal.voice.elevenlabs.ElevenLabsStreamTTS", + _make_tts_class(chunk=b"\x01\x02" * 800, num_chunks=2), + ) + + app = create_app() + with TestClient(app) as client: + messages, frames = await _rtc_call(client, config={"turn_detector": "heuristic"}) + + types = [m["type"] for m in messages] + started = next(m for m in messages if m["type"] == "session_started") + assert started["transport"] == "webrtc" + assert started["playback_acks"] == "native" + assert "transcript_committed" in types + assert "agent_text_done" in types + assert types[-1] == "session_ended" + # TTS rides the audio track, never the data channel. + assert "audio" not in types + # Media actually flowed: the downlink track delivered paced frames. + assert len(frames) > 10 + + async def test_error_before_handshake_still_reaches_the_client( + self, monkeypatch: pytest.MonkeyPatch, tmp_path: Path + ) -> None: + """A session that dies instantly must not vanish into a closed pc. + + The driver waits for the data channel before starting the session, so + even an immediate failure (here: STT connect raising, live: a bad API + key) is delivered as an error payload followed by session_ended. + """ + + class _BrokenSTT(SpeechToText): + def __init__(self, api_key: Any = None) -> None: + pass + + async def connect(self, config: AudioInputConfig) -> None: + raise RuntimeError("bad credentials") + + async def push_audio(self, chunk: bytes) -> None: + pass + + async def commit(self) -> None: + pass + + async def events(self): + return + yield + + async def close(self) -> None: + pass + + _setup_env(monkeypatch, tmp_path) + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsRealtimeSTT", _BrokenSTT) + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsStreamTTS", _make_tts_class()) + + app = create_app() + with TestClient(app) as client: + messages, _ = await _rtc_call(client) + + types = [m["type"] for m in messages] + assert "error" in types + assert types[-1] == "session_ended" + + +class TestVoiceRtcSignalingErrors: + def test_rejects_body_without_an_offer(self, monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: + _setup_env(monkeypatch, tmp_path) + app = create_app() + with TestClient(app) as client: + resp = client.post("/voice/rtc", json={"type": "offer"}) + assert resp.status_code == 400 + + async def test_rejects_offer_without_an_audio_track( + self, monkeypatch: pytest.MonkeyPatch, tmp_path: Path + ) -> None: + _setup_env(monkeypatch, tmp_path) + app = create_app() + + pc = RTCPeerConnection(configuration=RTCConfiguration(iceServers=[])) + pc.createDataChannel("events") # SCTP only, no mic + offer = await pc.createOffer() + await pc.setLocalDescription(offer) + try: + with TestClient(app) as client: + resp = await asyncio.to_thread( + client.post, + "/voice/rtc", + json={"sdp": pc.localDescription.sdp, "type": "offer"}, + ) + finally: + await pc.close() + assert resp.status_code == 400 + assert "audio track" in resp.json()["error"] + + def test_501_without_aiortc(self, monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: + import sys + + _setup_env(monkeypatch, tmp_path) + # Simulate a missing extra: None in sys.modules makes `from aiortc + # import ...` raise ImportError inside the route. + monkeypatch.setitem(sys.modules, "aiortc", None) + app = create_app() + with TestClient(app) as client: + resp = client.post("/voice/rtc", json={"sdp": "v=0", "type": "offer"}) + assert resp.status_code == 501 + assert "timbal[voice]" in resp.json()["error"] diff --git a/python/tests/voice/test_webrtc.py b/python/tests/voice/test_webrtc.py new file mode 100644 index 00000000..1beeacd4 --- /dev/null +++ b/python/tests/voice/test_webrtc.py @@ -0,0 +1,157 @@ +"""WebRTC transport primitives: pacing, played-axis accounting, resampling. + +The riskiest part of the WebRTC transport is the downlink pacing math — +``recv()`` timestamps drive both what the caller hears and what +interruption truncation believes was heard. These tests pin it in isolation, +before any signaling exists. +""" + +from __future__ import annotations + +import asyncio +import fractions +import time + +import pytest + +pytest.importorskip("aiortc", reason="timbal[voice] extra (aiortc) not installed") + +from aiortc.mediastreams import MediaStreamError # noqa: E402 +from av import AudioFrame # noqa: E402 +from timbal.voice.webrtc import PacedPlaybackTracker, PcmQueueTrack, track_to_pcm # noqa: E402 + +_SR = 16_000 +_FRAME_BYTES = int(_SR * 0.02) * 2 # 20ms of PCM16 mono + + +class TestPcmQueueTrack: + async def test_first_frame_is_immediate_then_paced_at_real_time(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + t0 = time.monotonic() + for _ in range(6): + await track.recv() + elapsed = time.monotonic() - t0 + # 6 frames = first immediate + 5 paced gaps of 20ms. + assert elapsed >= 0.5 * 5 * 0.02 # generous lower bound for CI jitter + assert elapsed < 1.0 + + async def test_empty_queue_yields_silence_and_no_played_bytes(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + frame = await track.recv() + assert bytes(frame.planes[0])[: _FRAME_BYTES] == b"\x00" * _FRAME_BYTES + assert frame.samples == int(_SR * 0.02) + assert frame.sample_rate == _SR + assert frame.time_base == fractions.Fraction(1, _SR) + assert track.played_bytes == 0 + + async def test_played_bytes_counts_real_pcm_only(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + track.write(b"\x01\x02" * (_FRAME_BYTES // 2)) # exactly one frame + track.write(b"\x03\x04" * 10) # 20 bytes: a partial second frame + f1 = await track.recv() + assert bytes(f1.planes[0])[:_FRAME_BYTES] == b"\x01\x02" * (_FRAME_BYTES // 2) + assert track.played_bytes == _FRAME_BYTES + f2 = await track.recv() + data = bytes(f2.planes[0])[:_FRAME_BYTES] + assert data[:20] == b"\x03\x04" * 10 + assert data[20:] == b"\x00" * (_FRAME_BYTES - 20) # silence pad + assert track.played_bytes == _FRAME_BYTES + 20 # pad not counted + + async def test_pts_advances_by_frame_samples(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + f1 = await track.recv() + f2 = await track.recv() + f3 = await track.recv() + step = int(_SR * 0.02) + assert (f1.pts, f2.pts, f3.pts) == (0, step, 2 * step) + + async def test_flush_drops_unsent_audio_and_freezes_played_axis(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + track.write(b"\x01\x02" * (_FRAME_BYTES // 2) * 3) + await track.recv() + assert track.played_bytes == _FRAME_BYTES + dropped = track.flush() + assert dropped == 2 * _FRAME_BYTES + assert track.buffered_bytes == 0 + assert track.played_bytes == _FRAME_BYTES # dropped audio was never heard + frame = await track.recv() # back to silence, still paced + assert bytes(frame.planes[0])[:_FRAME_BYTES] == b"\x00" * _FRAME_BYTES + + async def test_stopped_track_raises_media_stream_error(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + track.stop() + with pytest.raises(MediaStreamError): + await track.recv() + + +class TestPacedPlaybackTracker: + def test_position_is_native_truth(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + tracker = PacedPlaybackTracker(track) + assert tracker.ack_received is True + assert tracker.played_bytes == 0 + tracker.on_playback_ack(9999.0) # acks carry no information here + assert tracker.played_bytes == 0 + + async def test_reads_through_to_the_track(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + tracker = PacedPlaybackTracker(track) + track.write(b"\x01\x02" * _FRAME_BYTES) # two frames + tracker.on_audio_emitted(2 * _FRAME_BYTES) # no-op: counting is on dequeue + assert tracker.played_bytes == 0 + assert tracker.is_playing is True + await track.recv() + assert tracker.played_bytes == _FRAME_BYTES + + async def test_interruption_flushes_the_queue(self) -> None: + track = PcmQueueTrack(sample_rate=_SR) + tracker = PacedPlaybackTracker(track) + track.write(b"\x01\x02" * _FRAME_BYTES * 4) + await track.recv() + tracker.on_interrupted() + assert tracker.is_playing is False + assert track.buffered_bytes == 0 + assert tracker.played_bytes == _FRAME_BYTES + + +class _FrameSourceTrack: + """Duck-typed uplink track: replays canned AudioFrames, then ends.""" + + def __init__(self, frames: list[AudioFrame]) -> None: + self._frames = list(frames) + + async def recv(self) -> AudioFrame: + if not self._frames: + raise MediaStreamError + await asyncio.sleep(0) + return self._frames.pop(0) + + +def _mic_frame(pts: int, *, rate: int = 48_000, samples: int = 960, fill: bytes = b"\x11\x22") -> AudioFrame: + frame = AudioFrame(format="s16", layout="mono", samples=samples) + frame.planes[0].update(fill * samples) + frame.pts = pts + frame.sample_rate = rate + frame.time_base = fractions.Fraction(1, rate) + return frame + + +class TestTrackToPcm: + async def test_resamples_48k_mic_to_16k_session_pcm(self) -> None: + n_frames = 25 # 500ms of 48k audio + frames = [_mic_frame(i * 960) for i in range(n_frames)] + out = b"".join([chunk async for chunk in track_to_pcm(_FrameSourceTrack(frames), sample_rate=_SR)]) + expected = int(n_frames * 0.02 * _SR) * 2 # 500ms at 16k PCM16 + # The resampler's filter delay holds back a tail; allow one frame. + assert abs(len(out) - expected) <= _FRAME_BYTES + assert len(out) % 2 == 0 + + async def test_ends_cleanly_when_the_track_ends(self) -> None: + agen = track_to_pcm(_FrameSourceTrack([]), sample_rate=_SR) + chunks = [c async for c in agen] + assert chunks == [] + + async def test_passthrough_at_native_rate(self) -> None: + frames = [_mic_frame(i * 320, rate=_SR, samples=320) for i in range(10)] + out = b"".join([chunk async for chunk in track_to_pcm(_FrameSourceTrack(frames), sample_rate=_SR)]) + assert abs(len(out) - 10 * 320 * 2) <= _FRAME_BYTES diff --git a/python/timbal/server/README.md b/python/timbal/server/README.md index b07cd40b..7e239c5f 100644 --- a/python/timbal/server/README.md +++ b/python/timbal/server/README.md @@ -168,5 +168,39 @@ Once per turn — after `agent_text_done`, and also when the turn is interrupted ### What this is not - Not the bundled **`GET /voice/`** HTML demo — only the **`/voice/ws`** contract. -- Not REST/SSE for the live voice loop; real-time voice uses this WebSocket. +- Not REST/SSE for the live voice loop; real-time voice uses this WebSocket (or WebRTC, below). - The LLM/agent runs on the server; the client only captures audio, plays TTS, and renders text events. + +## Voice over WebRTC: `POST /voice/rtc` + +The same voice session over WebRTC instead of a WebSocket. Requires the **`timbal[voice]`** extra (which ships aiortc) on the server — without it the route answers **501** with an install hint. The bundled playground has a transport dropdown that exercises this path. + +**Why choose it over `/voice/ws`:** Opus instead of raw PCM (~10x less bandwidth), jitter buffering and packet-loss concealment on lossy/mobile networks, and **server-paced playback** — the server sends TTS at real time from its own clock, so it always knows exactly what the caller has heard. Barge-in truncation (`interrupted.heard_text`, memory truncation) is exact with **no playback acks**, and the unspoken tail of an interrupted reply is dropped server-side instead of asking the client to clear buffers. + +### Signaling + +One HTTP round trip, WHIP-style — no trickle ICE (wait for ICE gathering to complete before posting the offer): + +``` +POST /voice/rtc +{ "sdp": "", "type": "offer", "config": { ...same keys as the WS config frame... } } + +200 → { "sdp": "", "type": "answer" } +400 → bad offer / no audio track / runnable is not an Agent +501 → timbal[voice] extra (aiortc) not installed +``` + +The offer **must** contain: + +- **One audio track** — the mic. Sent Opus-encoded; the server decodes and resamples to the session rate, so the client-side `sample_rate` config key is irrelevant on this transport. Keep `echoCancellation: true` in `getUserMedia` constraints. +- **A data channel** (any label) — created by the client so its SCTP m-line rides the offer. All non-audio session events arrive here as JSON: the exact payloads of the WS protocol, except there are **no `audio` messages** (TTS is a real audio track the browser plays natively) and **no `playback` acks** (`session_started.playback_acks` is `"native"`, and `transport` is `"webrtc"`). + +The server answers with the TTS audio track on the same m-line. Client teardown = close the peer connection; server teardown (session end/error) closes the connection and fires `session_ended` on the data channel first. + +### ICE configuration + +| Env var | Meaning | +|---|---| +| `TIMBAL_STUN_URL` | STUN server; defaults to `stun:stun.l.google.com:19302`. Set to empty to disable (loopback/LAN). | +| `TIMBAL_TURN_URL` | Optional TURN server for clients behind symmetric NATs. | +| `TIMBAL_TURN_USERNAME` / `TIMBAL_TURN_PASSWORD` | TURN credentials. | diff --git a/python/timbal/server/http.py b/python/timbal/server/http.py index b715d3c6..07cf3077 100644 --- a/python/timbal/server/http.py +++ b/python/timbal/server/http.py @@ -80,9 +80,11 @@ def create_app() -> FastAPI: allow_headers=["*"], ) + from .rtc import router as rtc_router from .voice import router as voice_router app.include_router(voice_router) + app.include_router(rtc_router) @app.get("/healthcheck") async def healthcheck() -> Response: diff --git a/python/timbal/server/rtc.py b/python/timbal/server/rtc.py new file mode 100644 index 00000000..ed8c2371 --- /dev/null +++ b/python/timbal/server/rtc.py @@ -0,0 +1,212 @@ +"""Voice over WebRTC — offer/answer signaling for the same runnable as ``/voice/ws``. + +``POST /voice/rtc`` takes ``{"sdp": ..., "type": "offer", "config": {...}}`` +(``config`` uses the same keys as the WebSocket hello) and returns the SDP +answer — WHIP-style, one round trip, no trickle ICE (aiortc finishes +gathering before answering). + +Protocol expectations for clients: + +* The offer must contain one audio track (the mic) **and** a data channel — + the channel rides the offer's SCTP m-line, so the client creates it; the + server binds to whatever channel arrives, whatever its label. +* Session events arrive as JSON on the data channel — the same payloads as + the WebSocket transport, except ``audio``: TTS is a real audio track here, + paced by the server, so there are no base64 audio messages and **no + playback acks** — the server's own pacing clock is the played position, + which makes barge-in ``heard_text`` exact instead of estimated. + +Requires the ``timbal[voice]`` extra (aiortc); the route answers 501 without it. +""" + +from __future__ import annotations + +import asyncio +import contextlib +import json +import os +from contextlib import aclosing +from typing import Any + +import structlog +from fastapi import APIRouter, Request +from fastapi.responses import JSONResponse + +from .voice import build_voice_session, event_to_payloads, merge_client_voice_overrides + +logger = structlog.get_logger("timbal.server.rtc") + +router = APIRouter(prefix="/voice", tags=["voice"]) + +# Peer connections (and their driver tasks) stay alive via these references; +# entries are discarded when the session driver tears the connection down. +_pcs: set[Any] = set() +_drivers: set[asyncio.Task] = set() + + +def _ice_servers() -> list[Any]: + from aiortc import RTCIceServer + + servers = [] + # Empty TIMBAL_STUN_URL disables STUN (loopback/tests); unset keeps the default. + stun_url = os.environ.get("TIMBAL_STUN_URL", "stun:stun.l.google.com:19302") + if stun_url: + servers.append(RTCIceServer(urls=stun_url)) + turn_url = os.environ.get("TIMBAL_TURN_URL") + if turn_url: + servers.append( + RTCIceServer( + urls=turn_url, + username=os.environ.get("TIMBAL_TURN_USERNAME"), + credential=os.environ.get("TIMBAL_TURN_PASSWORD"), + ) + ) + return servers + + +@router.post("/rtc") +async def voice_rtc(request: Request) -> JSONResponse: + try: + from aiortc import RTCConfiguration, RTCPeerConnection, RTCSessionDescription + + from ..voice.webrtc import PacedPlaybackTracker, PcmQueueTrack, track_to_pcm + except ImportError: + return JSONResponse( + status_code=501, + content={"error": "The WebRTC voice transport requires the timbal[voice] extra."}, + ) + + from ..core.agent import Agent + from ..voice import AudioOutput + + body = await request.json() + sdp = body.get("sdp") + if not isinstance(sdp, str) or body.get("type") != "offer": + return JSONResponse(status_code=400, content={"error": "Body must carry an SDP offer."}) + config = body.get("config") + if not isinstance(config, dict): + config = {} + + runnable = request.app.state.runnable + if not isinstance(runnable, Agent): + logger.error("voice_rtc_rejected", reason="runnable is not an Agent", type=type(runnable).__name__) + return JSONResponse(status_code=400, content={"error": "Voice requires an Agent runnable."}) + + defaults: dict = getattr(request.app.state, "voice_config", None) or {} + sample_rate = int(merge_client_voice_overrides(defaults, config).get("sample_rate", 16_000)) + + downlink = PcmQueueTrack(sample_rate=sample_rate) + session, meta = build_voice_session( + runnable, defaults, config, playback_tracker=PacedPlaybackTracker(downlink) + ) + meta = {"playback_acks": "native", "transport": "webrtc", **meta} + + pc = RTCPeerConnection(configuration=RTCConfiguration(iceServers=_ice_servers())) + _pcs.add(pc) + + mic_track: Any = None + channel: Any = None + channel_ready = asyncio.Event() + # Session events can fire before SCTP is up; buffer until the client's + # data channel arrives. + pending_payloads: list[str] = [] + + def _dc_send(payload: dict) -> None: + msg = json.dumps(payload) + if channel is not None and channel.readyState == "open": + try: + channel.send(msg) + except Exception as e: + logger.debug("voice_rtc_dc_send_failed", error=str(e), msg_type=payload.get("type")) + else: + pending_payloads.append(msg) + + @pc.on("track") + def on_track(track: Any) -> None: + nonlocal mic_track + if track.kind == "audio" and mic_track is None: + mic_track = track + + @pc.on("datachannel") + def on_datachannel(ch: Any) -> None: + nonlocal channel + channel = ch + for msg in pending_payloads: + try: + ch.send(msg) + except Exception as e: + logger.debug("voice_rtc_dc_flush_failed", error=str(e)) + break + pending_payloads.clear() + channel_ready.set() + + @pc.on("connectionstatechange") + async def on_connectionstatechange() -> None: + logger.debug("voice_rtc_connection_state", state=pc.connectionState) + if pc.connectionState in ("failed", "closed"): + # Client is gone: end the session now rather than waiting for the + # STT provider to time out on silence. Idempotent when the driver + # already closed it. + await session.close() + + try: + await pc.setRemoteDescription(RTCSessionDescription(sdp=sdp, type="offer")) + except Exception as e: + _pcs.discard(pc) + logger.warning("voice_rtc_bad_offer", error=str(e)) + return JSONResponse(status_code=400, content={"error": f"Invalid SDP offer: {e}"}) + + if mic_track is None: + _pcs.discard(pc) + with contextlib.suppress(Exception): + await pc.close() + return JSONResponse(status_code=400, content={"error": "Offer must contain an audio track."}) + + # After setRemoteDescription, so the TTS track reuses the offer's audio + # transceiver instead of adding a second m-line the client never offered. + pc.addTrack(downlink) + + async def _drive() -> None: + # Do not start the session before the transport is usable: STT starts + # its clock on connect, and a session that dies immediately (bad API + # key) must still get its error payload to a client whose SCTP + # handshake hasn't finished. ICE failure lands in + # connectionstatechange, so this only times out on a client that + # connected but never offered a data channel. + try: + await asyncio.wait_for(channel_ready.wait(), timeout=15.0) + except TimeoutError: + logger.warning("voice_rtc_no_datachannel") + with contextlib.suppress(Exception): + await pc.close() + _pcs.discard(pc) + return + mic_pcm = track_to_pcm(mic_track, sample_rate=sample_rate) + try: + async with aclosing(session.run(mic_pcm)) as events: + async for event in events: + if isinstance(event, AudioOutput): + downlink.write(event.data) + continue + for payload in event_to_payloads(event, session, meta): + _dc_send(payload) + except Exception as e: + logger.error("voice_rtc_session_error", error=str(e), exc_info=True) + finally: + downlink.stop() + with contextlib.suppress(Exception): + await pc.close() + _pcs.discard(pc) + logger.info("voice_rtc_disconnected") + + driver = asyncio.create_task(_drive()) + _drivers.add(driver) + driver.add_done_callback(_drivers.discard) + + answer = await pc.createAnswer() + # Completes ICE gathering before returning — the answer is complete. + await pc.setLocalDescription(answer) + logger.info("voice_rtc_connected") + return JSONResponse( + content={"sdp": pc.localDescription.sdp, "type": pc.localDescription.type} + ) diff --git a/python/timbal/server/voice.html b/python/timbal/server/voice.html index 9f0195a3..e99518e3 100644 --- a/python/timbal/server/voice.html +++ b/python/timbal/server/voice.html @@ -102,6 +102,13 @@ border-color: var(--primary); box-shadow: 0 0 0 3px rgba(0,0,0,.07); } + .panel select:disabled { + color: var(--text-muted); + background: var(--bg); + border-color: var(--border); + cursor: not-allowed; + opacity: 0.65; + } .model-picker { display: flex; flex-direction: column; @@ -601,6 +608,13 @@

Voice session

+

Echo cancellation stays on in every mode. Settings apply on the next Start.

@@ -633,6 +647,28 @@

Voice session

localStorage.setItem(TD_STORAGE_KEY, tdSelect.value); }; +const transportSelect = document.getElementById('transport-select'); +const TRANSPORT_STORAGE_KEY = 'timbal-voice-transport'; +transportSelect.value = new URLSearchParams(location.search).get('transport') + || localStorage.getItem(TRANSPORT_STORAGE_KEY) || 'ws'; +if (!transportSelect.value) transportSelect.value = 'ws'; +function syncNsForTransport() { + // WebRTC sends the raw mic track, so the worklet's RNNoise output never + // reaches the wire — the transport forces browser noise suppression + // (startMic mirrors this). Gray the control out instead of lying with it. + const rtc = transportSelect.value === 'webrtc'; + nsSelect.disabled = rtc; + nsSelect.title = rtc + ? 'Not configurable over WebRTC — the browser applies its own noise suppression to the mic track.' + : "Mic noise suppression — applied on the next Start. Echo cancellation stays on in every mode."; +} +transportSelect.onchange = () => { + // Applied on the next Start — a live session keeps its transport. + localStorage.setItem(TRANSPORT_STORAGE_KEY, transportSelect.value); + syncNsForTransport(); +}; +syncNsForTransport(); + const sttSelect = document.getElementById('stt-select'); const STT_STORAGE_KEY = 'timbal-voice-stt-provider'; sttSelect.value = localStorage.getItem(STT_STORAGE_KEY) || ''; @@ -822,6 +858,8 @@

Voice session

} let ws, audioCtx, micStream, worklet, analyser, currentSource, meterRAF; +/** WebRTC transport state: the peer connection and the element playing the server's TTS track. */ +let pc = null, remoteAudioEl = null; /** False until WS is open, config frame sent, and AudioContext is running (worklet processes mic). */ let micAudioToWs = false; let nextPlayTime = 0; @@ -1098,7 +1136,9 @@

Voice session

if (analyser) { analyser.disconnect(); analyser = null; } if (micStream) { micStream.getTracks().forEach(t => t.stop()); micStream = null; } - const nsMode = nsSelect.value; + // WebRTC ships the raw getUserMedia track; RNNoise lives in the worklet + // and would be silently bypassed — force the browser suppressor instead. + const nsMode = transportSelect.value === 'webrtc' ? 'browser' : nsSelect.value; let useRnnoise = nsMode === 'rnnoise'; if (useRnnoise && rnnoiseAssets === null) { try { @@ -1199,7 +1239,12 @@

Voice session

micSelect.onchange = () => { if (ws && ws.readyState === WebSocket.OPEN) ws.send(JSON.stringify({type: 'mic_change'})); - startMic(micSelect.value); + void startMic(micSelect.value).then(() => { + // On WebRTC the pc holds the (now stopped) old track — swap in the new one. + const track = micStream?.getAudioTracks()[0]; + const sender = pc?.getSenders?.().find((s) => s.track?.kind === 'audio'); + if (sender && track) void sender.replaceTrack(track); + }); }; navigator.mediaDevices.addEventListener('devicechange', async () => { @@ -1252,6 +1297,17 @@

Voice session

sock.onmessage = null; try { sock.close(); } catch (_) {} } + if (pc) { + const conn = pc; + pc = null; + conn.onconnectionstatechange = null; + conn.ontrack = null; + try { conn.close(); } catch (_) {} + } + if (remoteAudioEl) { + try { remoteAudioEl.pause(); remoteAudioEl.srcObject = null; } catch (_) {} + remoteAudioEl = null; + } if (worklet) { try { worklet.disconnect(); } catch (_) {} worklet = null; } if (currentSource) { try { currentSource.disconnect(); } catch (_) {} currentSource = null; } if (micStream) { micStream.getTracks().forEach(t => t.stop()); micStream = null; } @@ -1300,6 +1356,30 @@

Voice session

void startSession(); }; +/** Config keys shared by the WS hello and the RTC offer body. */ +function sessionConfigPayload() { + const cfg = {}; + if (tdSelect.value) cfg.turn_detector = tdSelect.value; + if (sttSelect.value) cfg.stt_provider = sttSelect.value; + if (modelSelect.value) cfg.model = modelSelect.value; + return cfg; +} + +/** Fresh-session UI/playback state, shared by both transports. */ +function resetSessionUi() { + transcriptEl.innerHTML = ''; + window._assistantEl = null; + window._lastAssistantEl = null; + window._turnBubbles = []; + window._replyDone = false; + partialEl = null; + statusEl = null; + resetPlaybackTracking(); + suppressAssistantAudio = false; + stopAssistantAudio(); + sessionReady = false; +} + async function start() { const gen = startGen; setConn('connecting', 'Getting ready', 'Microphone and server connection…'); @@ -1317,6 +1397,11 @@

Voice session

await populateDevices(); } + if (transportSelect.value === 'webrtc') { + await startRtc(gen); + return; + } + setConn('connecting', 'Connecting', 'Opening WebSocket to this server…'); const proto = location.protocol === 'https:' ? 'wss' : 'ws'; micAudioToWs = false; @@ -1338,23 +1423,9 @@

Voice session

const ctxRate = audioCtx ? Math.round(audioCtx.sampleRate) : SAMPLE_RATE; const sr = rnnoiseCtxActive ? Math.round(ctxRate / 3) : ctxRate; sessionSampleRate = sr; - const hello = { sample_rate: sr }; - if (tdSelect.value) hello.turn_detector = tdSelect.value; - if (sttSelect.value) hello.stt_provider = sttSelect.value; - if (modelSelect.value) hello.model = modelSelect.value; - ws.send(JSON.stringify(hello)); - transcriptEl.innerHTML = ''; - window._assistantEl = null; - window._lastAssistantEl = null; - window._turnBubbles = []; - window._replyDone = false; - partialEl = null; - statusEl = null; + ws.send(JSON.stringify({ sample_rate: sr, ...sessionConfigPayload() })); + resetSessionUi(); setConn('live', 'Starting…', 'Loading STT / turn models (first session can take a few seconds)…'); - resetPlaybackTracking(); - suppressAssistantAudio = false; - stopAssistantAudio(); - sessionReady = false; if (playbackAckTimer) clearInterval(playbackAckTimer); playbackAckTimer = setInterval(() => sendPlaybackAck(false), PLAYBACK_ACK_INTERVAL_MS); const tryArmMic = async () => { @@ -1420,7 +1491,13 @@

Voice session

console.error('voice ws: bad json', err); return; } - switch (msg.type) { + handleServerMessage(msg); + }; +} + +/** One handler for both transports: WS frames and RTC data-channel messages. */ +function handleServerMessage(msg) { + switch (msg.type) { case 'session_started': sessionReady = true; { @@ -1531,8 +1608,95 @@

Voice session

case 'session_ended': setConn('ended', 'Session ended', 'Click Start for a new session.'); break; + } +} + +async function startRtc(gen) { + setConn('connecting', 'Connecting', 'Negotiating WebRTC with this server…'); + pc = new RTCPeerConnection(); + const conn = pc; + + // Raw mic track (browser AEC/NS applied via getUserMedia constraints). The + // worklet graph from startMic keeps driving the level meter; its PCM output + // goes nowhere because micAudioToWs stays false on this transport. + pc.addTrack(micStream.getAudioTracks()[0], micStream); + + // The server binds to whatever channel the offer carries — creating it + // here puts the SCTP m-line in the offer. + const dc = pc.createDataChannel('events'); + dc.onmessage = (e) => { + if (gen !== startGen) return; + let msg; + try { + msg = JSON.parse(e.data); + } catch (err) { + console.error('voice rtc: bad json', err); + return; } + handleServerMessage(msg); }; + + pc.ontrack = (e) => { + // TTS arrives as a real audio track: the browser handles decode, jitter + // and clock — no playPCM, no playback acks (the server paces playback + // itself, so barge-in truncation is exact without them). + remoteAudioEl = remoteAudioEl || new Audio(); + remoteAudioEl.autoplay = true; + remoteAudioEl.srcObject = e.streams[0] || new MediaStream([e.track]); + remoteAudioEl.play?.().catch(() => { /* autoplay policy — resumes on gesture */ }); + }; + + pc.onconnectionstatechange = () => { + if (gen !== startGen || pc !== conn) return; + if (['failed', 'closed', 'disconnected'].includes(conn.connectionState)) { + sessionReady = false; + micViz.classList.remove('active'); + if (connVisual === 'ended' || connVisual === 'error') { updateEmptyState(); return; } + if (userEndedSession) { + setConn('ended', 'Session ended', 'Click Start for a new session.'); + } else { + setConn('ended', 'Disconnected', 'Connection closed. Click Start for a new session.'); + } + updateEmptyState(); + } + }; + + const offer = await pc.createOffer(); + await pc.setLocalDescription(offer); + // One-round-trip signaling: wait for ICE gathering so the offer is complete + // (bounded — host candidates alone are enough against a local server). + if (pc.iceGatheringState !== 'complete') { + await new Promise((resolve) => { + const timer = setTimeout(resolve, 2000); + pc.addEventListener('icegatheringstatechange', () => { + if (conn.iceGatheringState === 'complete') { clearTimeout(timer); resolve(); } + }); + }); + } + if (gen !== startGen) return; + + const resp = await fetch('/voice/rtc', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ + sdp: conn.localDescription.sdp, + type: 'offer', + config: sessionConfigPayload(), + }), + }); + if (!resp.ok) { + let detail = `Server answered ${resp.status}.`; + try { detail = (await resp.json()).error || detail; } catch (_) {} + if (resp.status === 501) detail += ' Install it: uv pip install "timbal[voice]".'; + throw new Error(detail); + } + const answer = await resp.json(); + if (gen !== startGen) return; + await conn.setRemoteDescription(answer); + + resetSessionUi(); + setConn('live', 'Starting…', 'Loading STT / turn models (first session can take a few seconds)…'); + updateEmptyState(); } initRunnableStrip(); diff --git a/python/timbal/server/voice.py b/python/timbal/server/voice.py index edca0ae3..1e05c581 100644 --- a/python/timbal/server/voice.py +++ b/python/timbal/server/voice.py @@ -249,26 +249,25 @@ def select_turn_detector_spec(server_spec: Any, client_spec: Any, *, stt_is_flux return mode -@router.websocket("/ws") -async def voice_ws(ws: WebSocket) -> None: - from ..core.agent import Agent - from ..voice import ( - AgentStatus, - AgentTextDelta, - AgentTextDone, - AudioInputConfig, - AudioOutput, - AudioOutputConfig, - SessionEnded, - SessionError, - SessionInterrupted, - SessionStarted, - TranscriptCommitted, - TranscriptPartial, - TurnMetricsEvent, - VoiceSession, - VoiceSessionEvent, - ) +def build_voice_session( + runnable: Any, + defaults: dict[str, Any], + client_config: dict[str, Any], + *, + playback_tracker: Any = None, +) -> tuple[Any, dict[str, Any]]: + """Resolve voice config into a ``VoiceSession`` plus ``session_started`` metadata. + + Transport-agnostic: the WebSocket handler and the WebRTC route both call + this with their own client config dict. ``playback_tracker`` lets a paced + transport substitute its own position source for the default + client-acked estimate. + + Returns ``(session, meta)`` where ``meta`` holds the resolved identity + keys (``stt_provider``, ``stt_model``, ``model``, ``turn_detector``) that + transports include in their ``session_started`` payload. + """ + from ..voice import VoiceSession from ..voice.deepgram import ( DeepgramFluxSTT, effective_stt_model, @@ -276,57 +275,10 @@ async def voice_ws(ws: WebSocket) -> None: stt_provider_id, ) from ..voice.elevenlabs import ElevenLabsStreamTTS + from ..voice.session import AudioInputConfig, AudioOutputConfig + from ..voice.turn_detection import resolve_turn_detector - await ws.accept() - logger.info("voice_ws_connected") - - runnable = ws.app.state.runnable - if not isinstance(runnable, Agent): - logger.error("voice_ws_rejected", reason="runnable is not an Agent", type=type(runnable).__name__) - await ws.close(code=1008, reason="Voice requires an Agent runnable") - return - - audio_queue: asyncio.Queue[bytes] = asyncio.Queue() - - # Read the config hello. Protocol frames ("playback" acks, "audio", - # "mic_change") can race ahead of it; the hello is the only JSON message - # *without* a "type" field, so skip typed frames — however many arrive — - # until the hello shows up or the 2s deadline passes (a swallowed hello - # silently drops sample_rate / turn_detector overrides). A *binary* first - # frame means a client that streams raw PCM without a hello: start with - # defaults immediately instead of burning the deadline. - config: dict = {} - deadline = time.monotonic() + 2.0 - try: - while (remaining := deadline - time.monotonic()) > 0: - first = await asyncio.wait_for(ws.receive(), timeout=remaining) - if "text" in first and first["text"]: - # Per-frame errors (invalid JSON, malformed audio payload) must - # not end the scan: a valid hello may still be in flight. - try: - data = json.loads(first["text"]) - except ValueError as e: - logger.warning("voice_ws_bad_handshake_frame", error=str(e)) - continue - if isinstance(data, dict) and data.get("type") is not None: - if data.get("type") == "audio": - try: - await audio_queue.put(base64.b64decode(data["data"])) - except (KeyError, TypeError, ValueError) as e: - logger.warning("voice_ws_bad_handshake_frame", error=str(e)) - # Playback acks before any TTS audio carry no information. - continue - config = data if isinstance(data, dict) else {} - elif "bytes" in first and first["bytes"]: - await audio_queue.put(first["bytes"]) - break - except TimeoutError: - pass - except Exception as e: - logger.warning("voice_ws_first_frame_error", error=str(e)) - - defaults: dict = getattr(ws.app.state, "voice_config", None) or {} - merged = merge_client_voice_overrides(defaults, config) + merged = merge_client_voice_overrides(defaults, client_config) stt_provider = merged.get("stt_provider") stt_model_requested = merged.get("stt_model") @@ -376,12 +328,10 @@ async def voice_ws(ws: WebSocket) -> None: # come over the wire. When neither picks one, the server chooses by STT # rather than taking ``resolve_turn_detector``'s zero-dep default, because # only here is the STT's endpointing behaviour known. - from ..voice.turn_detection import resolve_turn_detector - turn_detector = None raw_td = select_turn_detector_spec( defaults.get("turn_detector"), - config.get("turn_detector"), + client_config.get("turn_detector"), stt_is_flux=stt_is_flux, ) if raw_td is not None: @@ -415,7 +365,7 @@ async def voice_ws(ws: WebSocket) -> None: str(runnable.model) if isinstance(getattr(runnable, "model", None), str) else None ) logger.info( - "voice_ws_session_config", + "voice_session_config", stt=type(stt).__name__, stt_provider=stt_provider, stt_model=stt_model, @@ -437,6 +387,8 @@ async def voice_ws(ws: WebSocket) -> None: if "turn_timeout_fallback" in merged: fb = merged["turn_timeout_fallback"] session_kwargs["turn_timeout_fallback"] = None if fb is None else str(fb) + if playback_tracker is not None: + session_kwargs["playback_tracker"] = playback_tracker session = VoiceSession( agent=runnable, stt=stt, @@ -448,6 +400,139 @@ async def voice_ws(ws: WebSocket) -> None: model=model_override, **session_kwargs, ) + meta = { + "stt_provider": stt_provider, + "stt_model": stt_model, + "model": llm_model, + "turn_detector": turn_detector_label, + } + return session, meta + + +def event_to_payloads(event: Any, session: Any, meta: dict[str, Any]) -> list[dict[str, Any]]: + """Map one ``VoiceSessionEvent`` to the JSON payloads a transport sends. + + Shared by the WebSocket handler and the WebRTC data channel — the wire + format is identical. ``AudioOutput`` is serialized as base64 here; a paced + transport (WebRTC) intercepts it *before* calling this and feeds the PCM + to its audio track instead. + + ``meta`` is the dict from :func:`build_voice_session`, extended by the + transport with its own keys (``transport``, ``playback_acks``). + """ + from ..voice import ( + AgentStatus, + AgentTextDelta, + AgentTextDone, + AudioOutput, + SessionEnded, + SessionError, + SessionInterrupted, + SessionStarted, + TranscriptCommitted, + TranscriptPartial, + TurnMetricsEvent, + ) + + if isinstance(event, SessionStarted): + return [ + { + "type": "session_started", + **meta, + # The endpointer arms during session startup (before this event + # is emitted), so this reflects the real state — not the + # requested config. + "vad_endpointing": session._endpointer is not None, + } + ] + if isinstance(event, TranscriptPartial): + return [{"type": "transcript_partial", "text": event.text}] + if isinstance(event, TranscriptCommitted): + payload: dict[str, Any] = {"type": "transcript_committed", "text": event.text} + if event.replace: + payload["replace"] = True + return [payload] + if isinstance(event, AgentStatus): + return [{"type": "agent_status", "text": event.text}] + if isinstance(event, AgentTextDelta): + return [{"type": "agent_text_delta", "text": event.text}] + if isinstance(event, AgentTextDone): + return [{"type": "agent_text_done", "text": event.text}] + if isinstance(event, AudioOutput): + return [{"type": "audio", "data": base64.b64encode(event.data).decode("ascii")}] + if isinstance(event, TurnMetricsEvent): + return [{"type": "metrics", "metrics": event.metrics.model_dump()}] + if isinstance(event, SessionInterrupted): + return [{"type": "interrupted", "heard_text": event.heard_text}] + if isinstance(event, SessionError): + return [{"type": "error", "message": event.message}] + if isinstance(event, SessionEnded): + return [ + { + "type": "session_transcript", + "entries": [e.model_dump() for e in session.transcript], + }, + {"type": "session_ended"}, + ] + return [] + + +@router.websocket("/ws") +async def voice_ws(ws: WebSocket) -> None: + from ..core.agent import Agent + from ..voice import SessionInterrupted, VoiceSessionEvent + + await ws.accept() + logger.info("voice_ws_connected") + + runnable = ws.app.state.runnable + if not isinstance(runnable, Agent): + logger.error("voice_ws_rejected", reason="runnable is not an Agent", type=type(runnable).__name__) + await ws.close(code=1008, reason="Voice requires an Agent runnable") + return + + audio_queue: asyncio.Queue[bytes] = asyncio.Queue() + + # Read the config hello. Protocol frames ("playback" acks, "audio", + # "mic_change") can race ahead of it; the hello is the only JSON message + # *without* a "type" field, so skip typed frames — however many arrive — + # until the hello shows up or the 2s deadline passes (a swallowed hello + # silently drops sample_rate / turn_detector overrides). A *binary* first + # frame means a client that streams raw PCM without a hello: start with + # defaults immediately instead of burning the deadline. + config: dict = {} + deadline = time.monotonic() + 2.0 + try: + while (remaining := deadline - time.monotonic()) > 0: + first = await asyncio.wait_for(ws.receive(), timeout=remaining) + if "text" in first and first["text"]: + # Per-frame errors (invalid JSON, malformed audio payload) must + # not end the scan: a valid hello may still be in flight. + try: + data = json.loads(first["text"]) + except ValueError as e: + logger.warning("voice_ws_bad_handshake_frame", error=str(e)) + continue + if isinstance(data, dict) and data.get("type") is not None: + if data.get("type") == "audio": + try: + await audio_queue.put(base64.b64decode(data["data"])) + except (KeyError, TypeError, ValueError) as e: + logger.warning("voice_ws_bad_handshake_frame", error=str(e)) + # Playback acks before any TTS audio carry no information. + continue + config = data if isinstance(data, dict) else {} + elif "bytes" in first and first["bytes"]: + await audio_queue.put(first["bytes"]) + break + except TimeoutError: + pass + except Exception as e: + logger.warning("voice_ws_first_frame_error", error=str(e)) + + defaults: dict = getattr(ws.app.state, "voice_config", None) or {} + session, meta = build_voice_session(runnable, defaults, config) + meta = {"playback_acks": "recommended", "transport": "websocket", **meta} async def _recv_loop() -> None: """Read frames from the browser and feed PCM into the audio queue.""" @@ -512,68 +597,16 @@ async def _send_json(data: dict) -> None: async def _handle(event: VoiceSessionEvent) -> None: """Forward session events to the browser over WebSocket.""" nonlocal warned_ack_degraded - if isinstance(event, SessionStarted): - # ``playback_acks`` advertises that the server understands - # ``{"type": "playback", "played_ms": ...}`` and expects clients that - # play audio to send them (see server/README.md). - await _send_json( - { - "type": "session_started", - "playback_acks": "recommended", - # Config id (``elevenlabs`` / ``deepgram-flux`` / …), not - # the STT class name — matches playground select values. - "stt_provider": stt_provider, - "stt_model": stt_model, - "model": llm_model, - "turn_detector": turn_detector_label, - # The endpointer arms during session startup (before this - # event is emitted), so this reflects the real state — not - # the requested config. - "vad_endpointing": session._endpointer is not None, - } + if isinstance(event, SessionInterrupted) and not warned_ack_degraded and not session.playback.ack_received: + warned_ack_degraded = True + logger.warning( + "voice_ws_truncation_degraded", + hint="client sent no playback acks before a barge-in; heard-text " + "truncation used the wall-clock estimate. Send " + '{"type": "playback", "played_ms": ...} every ~250ms while audio plays.', ) - elif isinstance(event, TranscriptPartial): - await _send_json({"type": "transcript_partial", "text": event.text}) - elif isinstance(event, TranscriptCommitted): - payload: dict = {"type": "transcript_committed", "text": event.text} - if event.replace: - payload["replace"] = True + for payload in event_to_payloads(event, session, meta): await _send_json(payload) - elif isinstance(event, AgentStatus): - await _send_json({"type": "agent_status", "text": event.text}) - elif isinstance(event, AgentTextDelta): - await _send_json({"type": "agent_text_delta", "text": event.text}) - elif isinstance(event, AgentTextDone): - await _send_json({"type": "agent_text_done", "text": event.text}) - elif isinstance(event, AudioOutput): - await _send_json( - { - "type": "audio", - "data": base64.b64encode(event.data).decode("ascii"), - } - ) - elif isinstance(event, TurnMetricsEvent): - await _send_json({"type": "metrics", "metrics": event.metrics.model_dump()}) - elif isinstance(event, SessionInterrupted): - if not warned_ack_degraded and not session.playback.ack_received: - warned_ack_degraded = True - logger.warning( - "voice_ws_truncation_degraded", - hint="client sent no playback acks before a barge-in; heard-text " - "truncation used the wall-clock estimate. Send " - '{"type": "playback", "played_ms": ...} every ~250ms while audio plays.', - ) - await _send_json({"type": "interrupted", "heard_text": event.heard_text}) - elif isinstance(event, SessionError): - await _send_json({"type": "error", "message": event.message}) - elif isinstance(event, SessionEnded): - await _send_json( - { - "type": "session_transcript", - "entries": [e.model_dump() for e in session.transcript], - } - ) - await _send_json({"type": "session_ended"}) recv_task = asyncio.create_task(_recv_loop()) try: diff --git a/python/timbal/voice/webrtc.py b/python/timbal/voice/webrtc.py new file mode 100644 index 00000000..ad55a4cc --- /dev/null +++ b/python/timbal/voice/webrtc.py @@ -0,0 +1,181 @@ +"""WebRTC transport primitives for :class:`~timbal.voice.VoiceSession`. + +Requires the ``timbal[voice]`` extra (aiortc ships with it). This module is +imported only by the RTC server route and its tests, so ``timbal.voice`` +stays importable without the extra. + +The session itself needs nothing from here — it already exposes the three +transport seams (audio-in iterable, events-out iterator, +:class:`~timbal.voice.playback.PlaybackTracker`). What WebRTC changes is +*who* paces the audio: the server's RTP sender pulls 20ms frames in real +time, so the played position is transport-truth instead of a client-acked +estimate, and a barge-in can drop the unsent tail server-side instead of +asking the client to clear a buffer. + +Positions are exact up to the client's jitter buffer (tens of ms) — a frame +handed to the RTP sender is on the caller's speaker almost immediately. +""" + +from __future__ import annotations + +import asyncio +import fractions +import time +from collections.abc import AsyncIterator + +import structlog + +try: + from aiortc import MediaStreamTrack + from aiortc.mediastreams import MediaStreamError + from av import AudioFrame, AudioResampler +except ImportError as e: # pragma: no cover — exercised only without the extra + raise ImportError( + "The WebRTC voice transport requires the timbal[voice] extra: " + "uv pip install 'timbal[voice]'" + ) from e + +from .playback import PlaybackTracker + +logger = structlog.get_logger("timbal.voice.webrtc") + +_FRAME_SECS = 0.02 + + +class PcmQueueTrack(MediaStreamTrack): + """Downlink audio: a paced 20ms-frame source over a PCM16 byte queue. + + The session pushes TTS PCM (faster than real time) via :meth:`write`; the + RTP sender pulls frames via :meth:`recv`, which sleeps to hold a real-time + cadence. When the queue is empty, silence frames keep the stream + continuous — receivers treat a stalled track as a broken one, the same + lesson the replay harness feeder learned about STT websockets. + + Frames are emitted at the source rate; aiortc's Opus encoder resamples to + 48kHz itself, so no resampling happens here. + + ``played_bytes`` counts only *real* PCM dequeued into sent frames — + silence padding and audio dropped by :meth:`flush` never touch the played + axis. That is exactly the contract interruption truncation needs. + """ + + kind = "audio" + + def __init__(self, sample_rate: int = 16_000) -> None: + super().__init__() + if sample_rate <= 0: + raise ValueError("sample_rate must be positive") + self._sample_rate = sample_rate + self._samples_per_frame = int(sample_rate * _FRAME_SECS) + self._frame_bytes = self._samples_per_frame * 2 + self._buf = bytearray() + self._played_bytes = 0 + self._timestamp = 0 + self._started_at: float | None = None + + def write(self, pcm: bytes) -> None: + """Queue PCM16 mono bytes for paced sending.""" + if pcm: + self._buf.extend(pcm) + + def flush(self) -> int: + """Barge-in: drop everything not yet handed to the RTP sender. + + Returns the number of bytes discarded. The played position is + untouched — dropped audio was never heard. + """ + dropped = len(self._buf) + self._buf.clear() + return dropped + + @property + def sample_rate(self) -> int: + return self._sample_rate + + @property + def buffered_bytes(self) -> int: + """Real PCM queued but not yet sent.""" + return len(self._buf) + + @property + def played_bytes(self) -> int: + """Real PCM handed to the RTP sender so far (silence excluded).""" + return self._played_bytes + + async def recv(self) -> AudioFrame: + if self.readyState != "live": + raise MediaStreamError + + if self._started_at is None: + self._started_at = time.monotonic() + else: + self._timestamp += self._samples_per_frame + wait = self._started_at + (self._timestamp / self._sample_rate) - time.monotonic() + if wait > 0: + await asyncio.sleep(wait) + + chunk = bytes(self._buf[: self._frame_bytes]) + del self._buf[: len(chunk)] + self._played_bytes += len(chunk) + if len(chunk) < self._frame_bytes: + # Underrun (or idle): pad with silence. Not counted as played. + chunk += b"\x00" * (self._frame_bytes - len(chunk)) + + frame = AudioFrame(format="s16", layout="mono", samples=self._samples_per_frame) + frame.planes[0].update(chunk) + frame.pts = self._timestamp + frame.sample_rate = self._sample_rate + frame.time_base = fractions.Fraction(1, self._sample_rate) + return frame + + +class PacedPlaybackTracker(PlaybackTracker): + """Playback position read from the transport's pacing clock. + + No estimates, no client acks: the track knows exactly which bytes it has + handed to the RTP sender. ``on_audio_emitted`` is a no-op because the + session emits faster than real time — counting happens on dequeue, inside + the track. + """ + + def __init__(self, track: PcmQueueTrack) -> None: + self._track = track + + def on_audio_emitted(self, num_bytes: int) -> None: + pass + + def on_interrupted(self) -> None: + dropped = self._track.flush() + if dropped: + logger.debug("webrtc_playback_flushed", dropped_bytes=dropped) + + @property + def ack_received(self) -> bool: + return True + + @property + def played_bytes(self) -> int: + return self._track.played_bytes + + @property + def is_playing(self) -> bool: + return self._track.buffered_bytes > 0 + + +async def track_to_pcm(track: MediaStreamTrack, sample_rate: int = 16_000) -> AsyncIterator[bytes]: + """Uplink adapter: decoded mic frames → PCM16 mono bytes for ``session.run()``. + + Browser audio arrives Opus-decoded at 48kHz; the session's STT expects + PCM16 mono at ``sample_rate``. 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55823, upload-time = "2026-05-04T23:06:08.395Z" }, +] + [[package]] name = "pytest" version = "9.0.2" @@ -2214,6 +2359,7 @@ dependencies = [ [package.optional-dependencies] all = [ + { name = "aiortc", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "fastapi", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "huggingface-hub", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "libcst", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, @@ -2245,6 +2391,7 @@ server = [ { name = "websockets", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, ] voice = [ + { name = "aiortc", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "huggingface-hub", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "onnxruntime", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "transformers", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, @@ -2262,6 +2409,8 @@ dev = [ [package.metadata] requires-dist = [ + { name = "aiortc", marker = "extra == 'all'", specifier = ">=1.9.0" }, + { name = "aiortc", marker = "extra == 'voice'", specifier = ">=1.9.0" }, { name = "anthropic", specifier = ">=0.45.0" }, { name = "fastapi", marker = "extra == 'all'", specifier = ">=0.115.8" }, { name = "fastapi", marker = "extra == 'server'", specifier = ">=0.115.8" }, From d201fa02b52ff1c85e3be5556ed4809078c54deb Mon Sep 17 00:00:00 2001 From: berges99 Date: Tue, 28 Jul 2026 14:39:49 +0200 Subject: [PATCH 26/30] feat(voice): record every call as it was heard, with a timestamped transcript MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit One MP3 per session (mixed mono by default, split stereo optional) on the real call timeline: the mic is the clock, TTS drains against it, and a barge-in drops the unheard tail exactly like interrupted.heard_text does. Plus a JSON manifest (transcript offsets + TurnMetrics — the latency chips) and an async on_saved hook for platform upload. Server-config only; a client hello can never switch recording on or off. session_started gains session_id and session_transcript gains started_at/offset_ms so clients can join recordings to conversations. Co-authored-by: Cursor --- python/tests/server/test_voice_ws.py | 93 +++++++- python/tests/server/voice_env.py | 1 + python/tests/voice/test_recording.py | 314 +++++++++++++++++++++++++++ python/timbal/server/README.md | 44 +++- python/timbal/server/rtc.py | 1 + python/timbal/server/voice.py | 57 ++++- python/timbal/voice/recording.py | 305 ++++++++++++++++++++++++++ python/timbal/voice/session.py | 54 +++++ 8 files changed, 853 insertions(+), 16 deletions(-) create mode 100644 python/tests/voice/test_recording.py create mode 100644 python/timbal/voice/recording.py diff --git a/python/tests/server/test_voice_ws.py b/python/tests/server/test_voice_ws.py index 44b548b3..2d95a7ed 100644 --- a/python/tests/server/test_voice_ws.py +++ b/python/tests/server/test_voice_ws.py @@ -10,6 +10,7 @@ import asyncio import base64 +import json from collections.abc import AsyncIterator from pathlib import Path @@ -94,7 +95,7 @@ async def close(self) -> None: # --------------------------------------------------------------------------- -def _write_agent_module(tmp_path: Path, *, responses: list[str] | None = None) -> str: +def _write_agent_module(tmp_path: Path, *, responses: list[str] | None = None, extra: str = "") -> str: """Write a temp module with a TestModel Agent and return its import spec.""" resp_repr = repr(responses or ["Hello from agent!"]) mod = tmp_path / "voice_agent.py" @@ -102,6 +103,7 @@ def _write_agent_module(tmp_path: Path, *, responses: list[str] | None = None) - "from timbal import Agent\n" "from timbal.core.test_model import TestModel\n" f"agent = Agent(name='voice_test', model=TestModel(responses={resp_repr}), tools=[])\n" + + extra ) return f"{mod.resolve()}::agent" @@ -727,3 +729,92 @@ def test_audio_chunks_are_valid_base64_pcm( assert len(audio_msgs) == 1 decoded = base64.b64decode(audio_msgs[0]["data"]) assert decoded == pcm_chunk + + +class TestVoiceWsRecording: + """Call recording: server-defaults-only config → MP3 + manifest per session.""" + + def _run_session(self, monkeypatch, spec: str, hello: dict) -> list[dict]: + monkeypatch.setenv("TIMBAL_RUNNABLE", spec) + for k in VOICE_ENV_KEYS: + monkeypatch.delenv(k, raising=False) + monkeypatch.setattr( + "timbal.voice.elevenlabs.ElevenLabsRealtimeSTT", + _make_stt_class([TranscriptEvent(type="committed", text="Hello")]), + ) + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsStreamTTS", _make_tts_class()) + app = create_app() + with TestClient(app) as client: + with client.websocket_connect("/voice/ws") as ws: + ws.send_json(hello) + return _collect_ws_messages(ws) + + def test_server_configured_recording_writes_audio_and_manifest( + self, + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, + ) -> None: + pytest.importorskip("av", reason="timbal[voice] extra (av) not installed") + rec_dir = tmp_path / "recordings" + spec = _write_agent_module( + tmp_path, + responses=["Hi there!"], + extra=f"agent.voice_config = {{'recording': {{'dir': {str(rec_dir)!r}}}}}\n", + ) + messages = self._run_session(monkeypatch, spec, {"language": "en"}) + + started = next(m for m in messages if m["type"] == "session_started") + session_id = started["session_id"] + assert session_id + + # Files are finalized before session_ended reaches the client. + assert (rec_dir / f"{session_id}.mp3").exists() + manifest = json.loads((rec_dir / f"{session_id}.json").read_text()) + assert manifest["session_id"] == session_id + assert manifest["meta"]["transport"] == "websocket" + assert [e["role"] for e in manifest["transcript"]] == ["user", "assistant"] + assert all(e["offset_ms"] >= 0 for e in manifest["transcript"]) + + # The wire transcript carries the same timing info. + transcript = next(m for m in messages if m["type"] == "session_transcript") + assert transcript["started_at"] == pytest.approx(manifest["started_at"]) + assert all("offset_ms" in e for e in transcript["entries"]) + + def test_client_hello_cannot_switch_recording_on( + self, + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, + ) -> None: + rec_dir = tmp_path / "recordings" + spec = _write_agent_module(tmp_path) # no recording in server defaults + messages = self._run_session( + monkeypatch, spec, {"recording": {"dir": str(rec_dir)}} + ) + assert any(m["type"] == "session_ended" for m in messages) + assert not rec_dir.exists() + + def test_env_var_enables_recording( + self, + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, + ) -> None: + pytest.importorskip("av", reason="timbal[voice] extra (av) not installed") + rec_dir = tmp_path / "recordings" + spec = _write_agent_module(tmp_path) + monkeypatch.setenv("TIMBAL_RUNNABLE", spec) + for k in VOICE_ENV_KEYS: + monkeypatch.delenv(k, raising=False) + monkeypatch.setenv("TIMBAL_VOICE_RECORDING_DIR", str(rec_dir)) + monkeypatch.setattr( + "timbal.voice.elevenlabs.ElevenLabsRealtimeSTT", + _make_stt_class([TranscriptEvent(type="committed", text="Hello")]), + ) + monkeypatch.setattr("timbal.voice.elevenlabs.ElevenLabsStreamTTS", _make_tts_class()) + app = create_app() + with TestClient(app) as client: + with client.websocket_connect("/voice/ws") as ws: + ws.send_json({"language": "en"}) + messages = _collect_ws_messages(ws) + + started = next(m for m in messages if m["type"] == "session_started") + assert (rec_dir / f"{started['session_id']}.mp3").exists() diff --git a/python/tests/server/voice_env.py b/python/tests/server/voice_env.py index fce58c97..4993fe88 100644 --- a/python/tests/server/voice_env.py +++ b/python/tests/server/voice_env.py @@ -10,4 +10,5 @@ "ELEVENLABS_VOICE_ID", "TIMBAL_VOICE_ID", "TIMBAL_VOICE_LANGUAGE", + "TIMBAL_VOICE_RECORDING_DIR", ) diff --git a/python/tests/voice/test_recording.py b/python/tests/voice/test_recording.py new file mode 100644 index 00000000..bad5c706 --- /dev/null +++ b/python/tests/voice/test_recording.py @@ -0,0 +1,314 @@ +"""CallRecorder: timeline placement, mixing, truncation, and decode round-trips. + +Every assertion decodes the actual MP3 back and checks *where* energy sits on +the timeline — that's the recorder's whole job. Tolerances are generous +(100ms guard bands) because lame adds encoder delay/padding. +""" + +from __future__ import annotations + +import json +import math +from pathlib import Path + +import pytest + +pytest.importorskip("av", reason="timbal[voice] extra (av) not installed") +np = pytest.importorskip("numpy", reason="timbal[voice] extra (numpy) not installed") + +import av # noqa: E402 +from timbal.voice.recording import CallRecorder, build_manifest # noqa: E402 + +SR = 16_000 + + +def _tone(secs: float, freq: float = 440.0, amp: int = 12000) -> bytes: + n = int(secs * SR) + buf = bytearray() + for i in range(n): + v = int(amp * math.sin(2 * math.pi * freq * i / SR)) + buf += v.to_bytes(2, "little", signed=True) + return bytes(buf) + + +def _silence(secs: float) -> bytes: + return b"\x00" * (int(secs * SR) * 2) + + +def _decode(path: Path) -> np.ndarray: + """Decode to float32, shape (channels, samples).""" + chunks = [] + with av.open(str(path)) as container: + for frame in container.decode(audio=0): + arr = frame.to_ndarray() + if arr.dtype == np.int16: + arr = arr.astype(np.float32) / 32768.0 + if not frame.format.is_planar and frame.layout.nb_channels > 1: + arr = arr.reshape(-1, frame.layout.nb_channels).T + chunks.append(arr.astype(np.float32)) + return np.concatenate(chunks, axis=1) + + +def _rms(x: np.ndarray) -> float: + return float(np.sqrt(np.mean(np.square(x)))) if x.size else 0.0 + + +def _span(audio: np.ndarray, ch: int, t0: float, t1: float) -> np.ndarray: + return audio[ch, int(t0 * SR) : int(t1 * SR)] + + +class TestTimeline: + def test_agent_audio_lands_where_the_mic_clock_said(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + # 1s of quiet call, then the agent speaks 0.5s while the caller is silent. + rec.add_mic(_silence(1.0)) + rec.add_agent(_tone(0.5)) + rec.add_mic(_silence(1.0)) + assert rec.close(manifest=None) is not None + + audio = _decode(tmp_path / "call.mp3") + assert audio.shape[0] == 1 # mixed => mono + assert abs(audio.shape[1] / SR - 2.0) < 0.15 + assert _rms(_span(audio, 0, 0.1, 0.9)) < 0.01 # before: silence + assert _rms(_span(audio, 0, 1.1, 1.4)) > 0.1 # agent speaking + assert _rms(_span(audio, 0, 1.6, 1.9)) < 0.01 # after: silence again + + def test_mixed_layout_sums_both_voices(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + rec.add_agent(_tone(1.0, freq=300)) + rec.add_mic(_tone(1.0, freq=800)) # both talk over the same second + rec.close() + + audio = _decode(tmp_path / "call.mp3") + assert audio.shape[0] == 1 + assert _rms(audio[0]) > 0.3 # both voices present, no channel lost + + def test_split_layout_keeps_sides_separate(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR, layout="split") + rec.add_agent(_tone(1.0)) + rec.add_mic(_silence(1.0)) # caller silent while the agent talks + rec.close() + + audio = _decode(tmp_path / "call.mp3") + assert audio.shape[0] == 2 + assert _rms(audio[0]) < 0.02 # left = caller: silent + assert _rms(audio[1]) > 0.1 # right = agent: tone + + def test_close_drains_agent_audio_past_the_mic_timeline(self, tmp_path: Path) -> None: + """Call ends while TTS is still playing: the tail belongs in the file.""" + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + rec.add_mic(_silence(0.2)) + rec.add_agent(_tone(1.0)) + rec.close() + + audio = _decode(tmp_path / "call.mp3") + assert abs(audio.shape[1] / SR - 1.2) < 0.15 + + +class TestBargeInTruncation: + def test_dropped_tail_never_reaches_the_file(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + rec.add_agent(_tone(2.0)) # a long reply, synthesized instantly + rec.add_mic(_silence(0.5)) # 0.5s heard... + emitted = int(2.0 * SR) * 2 + heard = int(0.5 * SR) * 2 + dropped = rec.drop_agent_tail(emitted - heard) # ...then barge-in + assert dropped == emitted - heard + rec.add_mic(_silence(1.0)) # call continues + rec.close() + + audio = _decode(tmp_path / "call.mp3") + assert abs(audio.shape[1] / SR - 1.5) < 0.15 + assert _rms(_span(audio, 0, 0.1, 0.4)) > 0.1 # heard prefix present + assert _rms(_span(audio, 0, 0.7, 1.4)) < 0.01 # unheard tail gone + + def test_drop_clamps_to_the_queue(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + rec.add_agent(_tone(0.1)) + assert rec.drop_agent_tail(10**9) == int(0.1 * SR) * 2 + assert rec.agent_pending_bytes == 0 + rec.close() + + +class TestRobustness: + def test_odd_sized_chunks_stay_sample_aligned(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + tone = _tone(0.5) + rec.add_mic(tone[:333]) + rec.add_mic(tone[333:]) + rec.close() + audio = _decode(tmp_path / "call.mp3") + assert abs(audio.shape[1] / SR - 0.5) < 0.1 + + def test_close_is_idempotent_and_feeds_after_close_are_noops(self, tmp_path: Path) -> None: + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + rec.add_mic(_silence(0.2)) + first = rec.close() + rec.add_mic(_silence(1.0)) + rec.add_agent(_tone(1.0)) + assert rec.close() is first + + def test_rejects_bad_layout(self, tmp_path: Path) -> None: + with pytest.raises(ValueError, match="layout"): + CallRecorder(tmp_path / "call.mp3", layout="both") # type: ignore[arg-type] + + +class TestSessionIntegration: + async def test_session_writes_recording_manifest_and_fires_on_saved(self, tmp_path: Path) -> None: + import asyncio + from contextlib import aclosing + + from timbal import Agent + from timbal.core.test_model import TestModel + from timbal.voice.session import ( + AgentTextDone, + SessionStarted, + TranscriptEvent, + VoiceSession, + VoiceSessionEvent, + ) + + from .test_session import DelayedMockSTT, MockTTS + + saved: list = [] + + async def _on_saved(result) -> None: + saved.append(result) + + recorder = CallRecorder(tmp_path / "call.mp3", sample_rate=SR, on_saved=_on_saved) + stt = DelayedMockSTT() + session = VoiceSession( + agent=Agent(name="rec", model=TestModel(responses=["Hi there!"]), tools=[]), + stt=stt, + tts=MockTTS(chunk=b"\x01\x02" * 800, num_chunks=2), + recorder=recorder, + session_id="fixed-session-id", + ) + session.recording_meta = {"transport": "test", "model": "test/model"} + + events: list[VoiceSessionEvent] = [] + + async def _mic() -> object: + # A short burst of real mic PCM so the caller side has timeline. + for _ in range(5): + yield b"\x00" * 640 + await asyncio.sleep(0.01) + while not any(isinstance(e, AgentTextDone) for e in events): + await asyncio.sleep(0.01) + await stt.finish() + + async def _drive() -> None: + while not any(isinstance(e, SessionStarted) for e in events): + await asyncio.sleep(0.01) + await stt.inject(TranscriptEvent(type="committed", text="Hello")) + + async def _run() -> None: + async with aclosing(session.run(_mic())) as stream: + driver = asyncio.create_task(_drive()) + async for ev in stream: + events.append(ev) + await driver + + await asyncio.wait_for(_run(), timeout=10) + + audio_path = tmp_path / "call.mp3" + manifest_path = tmp_path / "call.json" + assert audio_path.exists() and manifest_path.exists() + assert saved and saved[0].audio_path == audio_path + + manifest = json.loads(manifest_path.read_text()) + assert manifest["session_id"] == "fixed-session-id" + assert manifest["meta"] == {"transport": "test", "model": "test/model"} + roles = [e["role"] for e in manifest["transcript"]] + assert roles == ["user", "assistant"] + assert all(e["offset_ms"] >= 0 for e in manifest["transcript"]) + assert manifest["audio"]["duration_secs"] > 0 + assert manifest["turns"] # per-turn latency metrics for the UI chips + + decoded = _decode(audio_path) + assert decoded.shape[1] > 0 + + +class TestSessionBargeIn: + async def test_interrupt_drops_the_unheard_tail_from_the_recording(self, tmp_path: Path) -> None: + import asyncio + from contextlib import aclosing + + from timbal import Agent + from timbal.core.test_model import TestModel + from timbal.voice.session import SessionStarted, TranscriptEvent, VoiceSession + + from .test_session import DelayedMockSTT, MockTTS + + recorder = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + stt = DelayedMockSTT() + # 4s of agent audio emitted near-instantly (TTS is faster than real time). + emitted_secs = 4.0 + session = VoiceSession( + agent=Agent(name="rec", model=TestModel(responses=["A very long reply"]), tools=[]), + stt=stt, + tts=MockTTS(chunk=b"\x01\x02" * (SR // 2), num_chunks=int(emitted_secs)), + recorder=recorder, + ) + + started = asyncio.Event() + + async def _mic() -> object: + await started.wait() + yield b"\x00" * 640 + + async def _drive() -> None: + while recorder.agent_pending_bytes == 0: + await asyncio.sleep(0.01) + # Barge-in almost immediately: nearly nothing was heard yet. + await session.interrupt() + assert recorder.agent_pending_bytes < int(1.0 * SR) * 2 + await stt.finish() + + async def _run() -> None: + async with aclosing(session.run(_mic())) as stream: + driver: asyncio.Task | None = None + async for ev in stream: + if isinstance(ev, SessionStarted): + started.set() + await stt.inject(TranscriptEvent(type="committed", text="Hello")) + driver = asyncio.create_task(_drive()) + if driver is not None: + await driver + + await asyncio.wait_for(_run(), timeout=10) + + audio = _decode(tmp_path / "call.mp3") + duration = audio.shape[1] / SR + assert 0 < duration < emitted_secs / 2 # the unheard tail never landed + + +class TestManifest: + def test_manifest_written_next_to_the_audio_with_refreshed_duration(self, tmp_path: Path) -> None: + from timbal.voice.session import TranscriptEntry + + rec = CallRecorder(tmp_path / "call.mp3", sample_rate=SR) + rec.add_mic(_silence(0.5)) + rec.add_agent(_tone(0.5)) # queued; drained by close() after manifest build + t0 = 1_000_000.0 + manifest = build_manifest( + session_id="abc123", + started_at=t0, + meta={"transport": "webrtc", "model": "test/model"}, + transcript=[ + TranscriptEntry(role="user", text="Hello", timestamp=t0 + 1.2), + TranscriptEntry(role="assistant", text="Hi!", timestamp=t0 + 2.5), + ], + turns=[], + recorder=rec, + ) + result = rec.close(manifest=manifest) + assert result is not None and result.manifest_path is not None + + saved = json.loads(result.manifest_path.read_text()) + assert saved["session_id"] == "abc123" + assert saved["meta"]["transport"] == "webrtc" + assert [e["offset_ms"] for e in saved["transcript"]] == [1200, 2500] + # 0.5s mic + 0.5s tail drained at close — not the pre-drain 0.5s. + assert abs(saved["audio"]["duration_secs"] - 1.0) < 0.1 + assert abs(result.duration_secs - 1.0) < 0.1 diff --git a/python/timbal/server/README.md b/python/timbal/server/README.md index 7e239c5f..f38c6f01 100644 --- a/python/timbal/server/README.md +++ b/python/timbal/server/README.md @@ -86,7 +86,7 @@ All downlink messages are **text JSON** with a **`type`** field. | `type` | Fields | Meaning | |-------------------------|---------------|--------| -| `session_started` | `playback_acks`, `stt_provider`, `stt_model`, `model`, `turn_detector`, `vad_endpointing` | Voice session is live; safe to show “listening”. `playback_acks: "recommended"` advertises the [playback ack](#playback-acks-client--server) protocol. `stt_provider` is the config id actually in effect (`elevenlabs` / `deepgram-flux` / `deepgram-nova`), not the Python class name. `turn_detector` is the class name of the detector actually in effect (e.g. `LocalAudioTurnDetector`). `vad_endpointing` is a bool: whether the local [VAD endpointing](#config-overrides) fast path actually armed for this session (not merely what was requested). | +| `session_started` | `session_id`, `playback_acks`, `stt_provider`, `stt_model`, `model`, `turn_detector`, `vad_endpointing` | Voice session is live; safe to show “listening”. `session_id` keys the session's [call recording](#call-recording) files and any platform-side conversation record. `playback_acks: "recommended"` advertises the [playback ack](#playback-acks-client--server) protocol. `stt_provider` is the config id actually in effect (`elevenlabs` / `deepgram-flux` / `deepgram-nova`), not the Python class name. `turn_detector` is the class name of the detector actually in effect (e.g. `LocalAudioTurnDetector`). `vad_endpointing` is a bool: whether the local [VAD endpointing](#config-overrides) fast path actually armed for this session (not merely what was requested). | | `transcript_partial` | `text` | Live STT (may change). | | `transcript_committed` | `text` | Final user transcript for the utterance. | | `agent_text_delta` | `text` | Streaming assistant text (captions / UI). | @@ -109,26 +109,28 @@ Right before the server sends `session_ended`, it sends a `session_transcript` m ```json { "type": "session_transcript", + "started_at": 1713099998.500, "entries": [ - { "role": "user", "text": "Hola, ¿qué tal?", "timestamp": 1713100000.123 }, - { "role": "assistant", "text": "¡Hola! Todo bien, ¿en qué puedo ayudarte?", "timestamp": 1713100002.456 }, - { "role": "user", "text": "Cuéntame una historia", "timestamp": 1713100010.789 }, - { "role": "assistant", "text": "Había una vez…", "timestamp": 1713100012.012 } + { "role": "user", "text": "Hola, ¿qué tal?", "timestamp": 1713100000.123, "offset_ms": 1623 }, + { "role": "assistant", "text": "¡Hola! Todo bien, ¿en qué puedo ayudarte?", "timestamp": 1713100002.456, "offset_ms": 3956 }, + { "role": "user", "text": "Cuéntame una historia", "timestamp": 1713100010.789, "offset_ms": 12289 }, + { "role": "assistant", "text": "Había una vez…", "timestamp": 1713100012.012, "offset_ms": 13512 } ] } ``` -Each entry has: +`started_at` is the session's wall-clock start (Unix seconds). Each entry has: | Field | Type | Description | |-------------|--------|-------------| | `role` | string | `"user"` or `"assistant"`. | | `text` | string | Final committed text for that turn. | | `timestamp` | float | Unix timestamp (seconds) when the text was committed. | +| `offset_ms` | int | Milliseconds since `started_at` — lines up with the call recording's playback position. | This lets the frontend persist the conversation without having to accumulate `transcript_committed` / `agent_text_done` messages itself. -**Audio recording** is available server-side via the `VoiceSession` Python API (`record_audio=True`) but is not sent over the WebSocket (PCM dumps are too large for a single JSON frame). Use the `session.input_audio` / `session.output_audio` properties to access raw PCM bytes after the session closes for server-side storage, conversion, or upload. +**Audio recording** is available server-side via the `VoiceSession` Python API (`record_audio=True`) but is not sent over the WebSocket (PCM dumps are too large for a single JSON frame). Use the `session.input_audio` / `session.output_audio` properties to access raw PCM bytes after the session closes for server-side storage, conversion, or upload. For a persistent, playable per-call file see [Call recording](#call-recording) below. ### Turn metrics @@ -204,3 +206,31 @@ The server answers with the TTS audio track on the same m-line. Client teardown | `TIMBAL_STUN_URL` | STUN server; defaults to `stun:stun.l.google.com:19302`. Set to empty to disable (loopback/LAN). | | `TIMBAL_TURN_URL` | Optional TURN server for clients behind symmetric NATs. | | `TIMBAL_TURN_USERNAME` / `TIMBAL_TURN_PASSWORD` | TURN credentials. | + +## Call recording + +Server-side, transport-agnostic (WS and WebRTC share the wiring): every session writes **one playable MP3** — the call as heard, on the call timeline — plus a **JSON manifest** with the timestamped transcript and per-turn latency metrics. This is the data an ElevenLabs-style conversation review UI needs: audio player, transcript entries at `offset_ms`, latency chips per turn. + +**Enable** (server-side only — client config frames cannot switch recording on or off): + +```python +# via the runnable, full control: +agent.voice_config = { + "recording": { + "dir": "recordings", # required — files land here + "layout": "mixed", # "mixed" (default): mono, both voices summed + # "split": stereo, caller left / agent right + "bitrate_kbps": 32, # MP3 bitrate (32 kbps mono ≈ 0.25 MB/min) + "on_saved": my_async_hook, # optional: async (RecordingResult) -> None + }, +} +``` + +or set **`TIMBAL_VOICE_RECORDING_DIR=recordings`** (dir only, defaults for the rest). Requires the `timbal[voice]` extra (av + numpy); without it the server logs a warning and runs the call unrecorded. + +Per session, keyed by the `session_id` from `session_started`: + +- **`{session_id}.mp3`** — mic and TTS mixed on the real call timeline. TTS synthesizes faster than real time, so the agent side is paced by the mic clock; on barge-in the **unheard tail is dropped** exactly like `interrupted.heard_text` truncates the text (exact on WebRTC, ack/estimate-based on WS). Encoded progressively — a crashed process still leaves a playable file. +- **`{session_id}.json`** — manifest: `session_id`, `started_at`/`ended_at`, resolved config (`transport`, `model`, `stt_provider`, ...), `transcript` entries with `offset_ms`, `turns` (the full `TurnMetrics` per turn), and the audio descriptor (`layout`, `sample_rate`, `bitrate_kbps`, `duration_secs`). + +`on_saved` fires after both files are written (e.g. upload to platform storage and delete the local copy); its failures are logged, never crash the session. diff --git a/python/timbal/server/rtc.py b/python/timbal/server/rtc.py index ed8c2371..cec21d30 100644 --- a/python/timbal/server/rtc.py +++ b/python/timbal/server/rtc.py @@ -100,6 +100,7 @@ async def voice_rtc(request: Request) -> JSONResponse: runnable, defaults, config, playback_tracker=PacedPlaybackTracker(downlink) ) meta = {"playback_acks": "native", "transport": "webrtc", **meta} + session.recording_meta = meta pc = RTCPeerConnection(configuration=RTCConfiguration(iceServers=_ice_servers())) _pcs.add(pc) diff --git a/python/timbal/server/voice.py b/python/timbal/server/voice.py index 1e05c581..b5869e57 100644 --- a/python/timbal/server/voice.py +++ b/python/timbal/server/voice.py @@ -37,7 +37,7 @@ def default_voice_config_from_env() -> dict[str, Any]: """STT/TTS defaults for ``/voice/ws`` (ElevenLabs). Override with env or ``runnable.voice_config``.""" - return { + cfg: dict[str, Any] = { "stt_provider": os.environ.get("TIMBAL_STT_PROVIDER", "elevenlabs"), "stt_model": os.environ.get("TIMBAL_STT_MODEL", "scribe_v2_realtime"), "tts_model": os.environ.get("TIMBAL_TTS_MODEL", "eleven_flash_v2_5"), @@ -55,6 +55,12 @@ def default_voice_config_from_env() -> dict[str, Any]: }, "tts_extra": {"auto_mode": True}, } + # Call recording (MP3 + manifest per session). The full dict form — with + # layout / bitrate_kbps / on_saved — comes via ``runnable.voice_config``. + recording_dir = os.environ.get("TIMBAL_VOICE_RECORDING_DIR") + if recording_dir: + cfg["recording"] = {"dir": recording_dir} + return cfg def merge_voice_config(runnable: Any) -> dict[str, Any]: @@ -389,6 +395,32 @@ def build_voice_session( session_kwargs["turn_timeout_fallback"] = None if fb is None else str(fb) if playback_tracker is not None: session_kwargs["playback_tracker"] = playback_tracker + + # Call recording is read from the *server* defaults only, never the merged + # dict — merge_client_voice_overrides applies client keys freely, and a + # browser must not be able to switch recording on or off. + recording_cfg = defaults.get("recording") + if isinstance(recording_cfg, dict) and recording_cfg.get("dir"): + try: + from uuid_extensions import uuid7 + + from ..voice.recording import CallRecorder + + session_id = uuid7(as_type="str").replace("-", "") + session_kwargs["session_id"] = session_id + session_kwargs["recorder"] = CallRecorder( + Path(recording_cfg["dir"]) / f"{session_id}.mp3", + sample_rate=int(merged.get("sample_rate", 16_000)), + layout=recording_cfg.get("layout", "mixed"), + bitrate_kbps=int(recording_cfg.get("bitrate_kbps", 32)), + on_saved=recording_cfg.get("on_saved"), + ) + except ImportError: + logger.warning("voice_recording_unavailable", hint="call recording requires timbal[voice] (av + numpy)") + except Exception as e: + # A misconfigured recorder must not take voice down with it. + logger.error("voice_recording_setup_failed", error=str(e), exc_info=True) + session = VoiceSession( agent=runnable, stt=stt, @@ -401,6 +433,7 @@ def build_voice_session( **session_kwargs, ) meta = { + "session_id": session.session_id, "stt_provider": stt_provider, "stt_model": stt_model, "model": llm_model, @@ -467,13 +500,20 @@ def event_to_payloads(event: Any, session: Any, meta: dict[str, Any]) -> list[di if isinstance(event, SessionError): return [{"type": "error", "message": event.message}] if isinstance(event, SessionEnded): - return [ - { - "type": "session_transcript", - "entries": [e.model_dump() for e in session.transcript], - }, - {"type": "session_ended"}, - ] + # Entries carry absolute wall-clock timestamps; offset_ms (relative to + # started_at) saves every client the subtraction — it's what a + # conversation-review UI actually renders. + started_at = getattr(session, "started_at", None) + entries = [] + for e in session.transcript: + d = e.model_dump() + if started_at is not None: + d["offset_ms"] = max(0, round((e.timestamp - started_at) * 1000)) + entries.append(d) + transcript_payload: dict[str, Any] = {"type": "session_transcript", "entries": entries} + if started_at is not None: + transcript_payload["started_at"] = started_at + return [transcript_payload, {"type": "session_ended"}] return [] @@ -533,6 +573,7 @@ async def voice_ws(ws: WebSocket) -> None: defaults: dict = getattr(ws.app.state, "voice_config", None) or {} session, meta = build_voice_session(runnable, defaults, config) meta = {"playback_acks": "recommended", "transport": "websocket", **meta} + session.recording_meta = meta async def _recv_loop() -> None: """Read frames from the browser and feed PCM into the audio queue.""" diff --git a/python/timbal/voice/recording.py b/python/timbal/voice/recording.py new file mode 100644 index 00000000..3fea5706 --- /dev/null +++ b/python/timbal/voice/recording.py @@ -0,0 +1,305 @@ +"""Call recording: one playable audio file per voice session, plus a manifest. + +The recorder reconstructs the *call as heard*, not the TTS as synthesized. +Mic PCM is the master clock — it arrives continuously in real time on both +transports — and every mic chunk drains an equal span of the agent's queued +TTS onto the same timeline (silence when the agent wasn't talking). TTS +synthesizes faster than real time, so the agent side is a queue; a barge-in +drops its unheard tail (:meth:`CallRecorder.drop_agent_tail`) exactly like +interruption truncation drops unheard text. + +Layouts: + +* ``"mixed"`` (default) — mono, both voices summed with a clipping guard. + Sounds like the call did; what a human reviewing the conversation wants. +* ``"split"`` — stereo, caller left / agent right. The call-center + convention for re-transcription/diarization where voice bleed matters. + +Output is MP3 (universal ``