How can I do speaker identification (diarization) with microsoft speech to text without previous voice enrollment?

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In my application, I need to record a conversation between people and there's no room in the physical workflow to take a 20 second sample of each person's voice for the purpose of training the recognizer, nor to ask each person to read a canned passphrase for training. But without doing that, as far as I can tell, there's no way to get speaker identification.

Is there any way to just record, say, 5 people speaking and have the recognizer automatically classify returned text as belonging to one of the 5 distinct people, without previous training?

(For what it's worth, IBM Watson can do this, although it doesn't do it very accurately, in my testing.)

microsoft-speech-platform microsoft-cognitive speech-to-text
2 Answers

If I understand your question right then Conversation Transcription should be a solution for your scenario, as it will show the speakers as Speaker[x] and iterate for each new speaker, if you don't generate user profiles beforehand.

User voice samples are optional. Without this input, the transcription will show different speakers, but shown as "Speaker1", "Speaker2", etc. instead of recognizing as pre-enrolled specific speaker names.

You can get started with the real-time conversation transcription quickstart.

user_81616700

Microsoft Conversation Transcription which is in Preview, now targeting to microphone array device. So the input recording should be recorded by a microphone array. If your recordings are from common microphone, it may not work and you need special configuration. You can also try Batch diarization which support offline transcription with diarizing 2 speakers for now, it will support 2+ speaker very soon, probably in this month.

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