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Merge branch 'adamnsandle' of github.com:snakers4/silero-vad into adamnsandle
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@@ -346,6 +346,7 @@ Since our VAD (only VAD, other networks are more flexible) was trained on chunks
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- `num_steps` - nubmer of overlapping windows to split audio chunk into (we recommend 4 or 8)
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- `num_samples_per_window` - number of samples in each window, our models were trained using `4000` samples (250 ms) per window, so this is preferable value (lesser values reduce [quality](https://github.com/snakers4/silero-vad/issues/2#issuecomment-750840434));
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- `min_speech_samples` - minimum speech chunk duration in samples
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- `min_silence_samples` - minimum silence duration in samples between to separate speech chunks
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Optimal parameters may vary per domain, but we provided a tiny tool to learn the best parameters. You can invoke `speech_timestamps` with visualize_probs=True (`pandas` required):
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