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have not found a way to extract unique speaker embeddings from the pipeline after running it.
it would allow to similarity function against existing saved speaker embeddings to identify speakers.
The text was updated successfully, but these errors were encountered:
Hi @Aduomas, you could get to the centroids (averaged embeddings) of the pipeline in this way:
pipeline = SpeakerDiarization() # inference over your stream centroids = pipeline.clustering.centers
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have not found a way to extract unique speaker embeddings from the pipeline after running it.
it would allow to similarity function against existing saved speaker embeddings to identify speakers.
The text was updated successfully, but these errors were encountered: