From d3693d8cb9afd2749726288c77b56538c46fb581 Mon Sep 17 00:00:00 2001 From: Fangjun Kuang Date: Tue, 24 May 2022 23:02:11 +0800 Subject: [PATCH] Typo fixes. --- README.md | 25 +++++++++++++++---------- 1 file changed, 15 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 57d96eef1..998708e16 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ C++; while IO-bound tasks, such as socket communication, are implemented in Python. **Caution**: We assume the model is trained using pruned stateless RNN-T -from [icefa][icefall] and it is from a directory like +from [icefall][icefall] and it is from a directory like `pruned_transducer_statelessX` where `X` >=2. ## Installation @@ -27,7 +27,8 @@ cd sherpa pip install -r ./requirements.txt ``` -Third, install C++ extension. You can use one of the following methods. +Third, install the C++ extension of `sherpa`. You can use one of +the following methods. ### Option 1: Use `pip` @@ -66,11 +67,12 @@ It should print the version of `sherpa`. To start the server, you need to first generate two files: -- (1) The torch script model file. You can use `export.py` in -`pruned_transducer_statelessX` from [icefall][icefall] +- (1) The torch script model file. You can use `export.py --jit=1` in +`pruned_transducer_statelessX` from [icefall][icefall]. - (2) The BPE model file. You can find it in `data/lang_bpe_XXX/bpe.model` -in icefall, where `XXX` the number of BPE tokens used in the training. +in [icefall][icefall], where `XXX` is the number of BPE tokens used in +the training. With the above two files ready, you can start the server with the following command: @@ -122,7 +124,7 @@ After starting the server, you can use the following command to start the client You can use `./sherpa/bin/offline_client.py --help` to view the usage message. -The following show how to use the client send some test waves to the server +The following shows how to use the client to send some test waves to the server for recognition. ```bash @@ -136,9 +138,12 @@ sherpa/bin/offline_client.py \ ### RTF test -We provide a demo `./sherpa/bin/decode_mainifest.py` to decode the test-clean -dataset from the LibriSpeech corpus. It creates 50 connections to the server -using websockets and sends audio files to the server for recognition. -At the end, it will show you the RTF and WER. +We provide a demo [./sherpa/bin/decode_mainifest.py](./sherpa/bin/decode_mainifest.py) +to decode the `test-clean` dataset from the LibriSpeech corpus. + +It creates 50 connections to the server using websockets and sends audio files +to the server for recognition. + +At the end, it will display the RTF and the WER. [icefall]: https://github.com/k2-fsa/icefall/