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AUTHOR Hervé Bredin - http://herve.niderb.fr
Manually annotating data for training is time consuming.
Luckily, pyannote.audio comes with a bunch of Prodigy recipes that should speed things up a bit.
The pyannote.sad.manual recipe will stream in .wav files in chunks and tag the detected speech regions as SPEECH.
You can then adjust the regions manually if needed.
The pyannote.dia.manual recipe will stream in .wav files and tag each speaker with its own SPEAKER_X tag.
You can then adjust and re-assign the regions manually if needed.
Note that, if you ran the pyannote.sad.manual recipe first, the manually adjusted speech regions boundaries will be used so that you can focus on the tagging part.
While the pyannote.dia.manual recipe might be useful is some cases, it might be impractical to use for longer files with lots of speakers.
The pyannote.dia.binary recipe will play two short excerpts of the manually adjusted speech regions from the pyannote.sad.manual recipe and ask you whether they were uttered by the same speaker.
Your answers will then be used to improve the initial suggestion of pyannote.dia.manual recipe.
In practice, they will serve as "cannot link" or "must link" constraints in the internal hierarchical agglomerative clustering part of the speaker diarization pipeline.
If you are using this feature, please consider supporting the development of pyannote.audio (either through Github Sponsors or via other ways) as I am not affiliated with Explosion and will not get any money from your purchase of a Prodigy license (nor be able to hire any academic researcher to further work on this).