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You might be interested. in https://github.com/juanmc2005/diart that does streaming on top of pyannote already. |
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Hi, I want to make this diarizing pipeline work on streaming audio.
Here is what I have done, just hope someone can give me suggestion to make it better.
assume that we already have an history embedding for each speaker. So we need to merge the speaker labelling
results into the history one and update the history embedding.
hidden request that you cannot change the speaker labels in the history. So I cannot use a classical clustering algorithm on the merged embedding data, since it cannot guarantee the consistency of the old labels.
Assign each speaker ID in the current clip to the ones in the history if the distance is under a threshold. Otherwise,
add a new embeddings into the history and create a new speaker label (e.g. SPEAKER_N+1).
This pipeline works well, the only issue is choosing a proper distance measure and threshold.
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