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speaker-diarization-v1

Voice Activity Detection
pyannote.audio
PyTorch
pyannote
pyannote-audio-model
audio
voice
speech
speaker
speaker-diarization
speaker-change-detection
speaker-segmentation
overlapped-speech-detection
resegmentation
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@@ -28,7 +28,7 @@ Consider switching to [pyannoteAI](https://www.pyannote.ai) for better and faste
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  This model ingests 10 seconds of mono audio sampled at 16kHz and outputs speaker diarization as a (num_frames, num_classes) matrix where the 7 classes are _non-speech_, _speaker #1_, _speaker #2_, _speaker #3_, _speakers #1 and #2_, _speakers #1 and #3_, and _speakers #2 and #3_.
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- ![Example output](example.png)
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  ```python
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  # waveform (first row)
 
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  This model ingests 10 seconds of mono audio sampled at 16kHz and outputs speaker diarization as a (num_frames, num_classes) matrix where the 7 classes are _non-speech_, _speaker #1_, _speaker #2_, _speaker #3_, _speakers #1 and #2_, _speakers #1 and #3_, and _speakers #2 and #3_.
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+ ![Example output](https://huggingface.co/pyannote/segmentation-3.0/blob/main/example.png)
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  ```python
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  # waveform (first row)