Handle audio files less than 10s long for speaker diarization. (#1412)

If the input audio file is less than 10 seconds long, there is only 
one chunk, and there is no need to compute embeddings or 
do clustering.

We can use the segmentation result from the speaker segmentation 
model directly.

sherpa-onnx/csrc/offline-speaker-diarization-pyannote-impl.h

@@ -99,6 +99,14 @@ class OfflineSpeakerDiarizationPyannoteImpl
 
     segmentations.clear();
 
+    if (labels.size() == 1) {
+      if (callback) {
+        callback(1, 1, callback_arg);
+      }
+
+      return HandleOneChunkSpecialCase(labels[0], n);
+    }
+
     // labels[i] is a 0-1 matrix of shape (num_frames, num_speakers)
 
     // speaker count per frame
@@ -201,7 +209,7 @@ class OfflineSpeakerDiarizationPyannoteImpl
     }
 
     int32_t num_chunks = (n - window_size) / window_shift + 1;
-    bool has_last_chunk = (n - window_size) % window_shift > 0;
+    bool has_last_chunk = ((n - window_size) % window_shift) > 0;
 
     ans.reserve(num_chunks + has_last_chunk);
 
@@ -524,9 +532,9 @@ class OfflineSpeakerDiarizationPyannoteImpl
       count(seq, Eigen::all).array() += labels[i].array();
     }
 
-    bool has_last_chunk = (num_samples - window_size) % window_shift > 0;
+    bool has_last_chunk = ((num_samples - window_size) % window_shift) > 0;
 
-    if (has_last_chunk) {
+    if (!has_last_chunk) {
       return count;
     }
 
@@ -622,6 +630,27 @@ class OfflineSpeakerDiarizationPyannoteImpl
     return ans;
   }
 
+  OfflineSpeakerDiarizationResult HandleOneChunkSpecialCase(
+      const Matrix2DInt32 &final_labels, int32_t num_samples) const {
+    const auto &meta_data = segmentation_model_.GetModelMetaData();
+    int32_t window_size = meta_data.window_size;
+    int32_t window_shift = meta_data.window_shift;
+    int32_t receptive_field_shift = meta_data.receptive_field_shift;
+
+    bool has_last_chunk = (num_samples - window_size) % window_shift > 0;
+    if (!has_last_chunk) {
+      return ComputeResult(final_labels);
+    }
+
+    int32_t num_frames = final_labels.rows();
+
+    int32_t new_num_frames = num_samples / receptive_field_shift;
+
+    num_frames = (new_num_frames <= num_frames) ? new_num_frames : num_frames;
+
+    return ComputeResult(final_labels(Eigen::seq(0, num_frames), Eigen::all));
+  }
+
   void MergeSegments(
       std::vector<OfflineSpeakerDiarizationSegment> *segments) const {
     float min_duration_off = config_.min_duration_off;