False Alarms vs Misses

[picheny-nyu]

I have a diarization application in which I prefer to have fewer false alarms at the expense of more misses. Can this be controlled during fine tuning?

Thanks Michael

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[hbredin]

Not in 3.x, no.

I am considering adding back the option but cannot provide an ETA though.

Can you say more about your use case?

[picheny-nyu]

Using the output to identify sections of speech in parent-toddler conversations to transcribe as input for unsupervised speech recognition fine-tuning. Figure better to miss questionable segments than train on false alarms.

[hbredin]

I would then use pyannote/segmentation for this purpose, wrapped in a voice activity detection pipeline that comes with onse/offset thresholds:

https://huggingface.co/pyannote/segmentation#voice-activity-detection

[picheny-nyu]

Thanks. I do need diarization, though - I want to process the adult and toddler speech separately. Would you suggest I just use a downleveled version of the diarization pipeline that still uses VAD?

[hbredin]

Yes.

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