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Thanks. Are you referring to Transcribe? https://aws.amazon.com/transcribe/ https://aws.amazon.com/transcribe/ Transcribe seems to be more for speech-to-text i

by achow 7y ago

Thanks. Are you referring to Transcribe? https://aws.amazon.com/transcribe/ https://aws.amazon.com/transcribe/ Transcribe seems to be more for speech-to-text irrespective to who is making the speech. Here the requirement is to identify the unique voices. Ex. if "Mary had a little lamb" is voiced by two different voices then the engine should identify Voice A said "Mary" at 00.00.00sec-00.00.01sec and then Voice B said "had a little" at 0.00.02sec-00.00.03sec, then Voice A again said "lamb".. etc.

gregsadetsky 7y ago
Transcribe does “Recognize Multiple Speakers” — it’s on the page that you linked to, in the list of features. I would also recommend comparing it to Google’s and maybe MS/Azure’s services. Aside from the fidelity of the transcription itself, and the accuracy of disambiguating the different speakers, I’m also not convinced that all of these services will give you an end timestamp (start timestamps are sometimes there, but not necessarily for every word or sentence). You could try a multi prong approach by doing the transcript to get text and speakers only (using the services mentioned above), and then using an aligner such as “gentle” [0] to find the start / end times. You will have some gaps and wrongly transcribed words, but it may be a start..! [0] https://github.com/lowerquality/gentle https://github.com/lowerquality/gentle
yorwba 7y ago
From your link: Recognize Multiple Speakers Amazon Transcribe is able to recognize when the speaker changes and attribute the transcribed text appropriately. This can significantly reduce the amount of work needed to transcribe audio with multiple speakers like telephone calls, meetings, and television shows. So they claim to be able to do it. However, having to do speaker diarization doesn't exactly make speech recognition easier, so you should adjust your expectations regarding the error rate accordingly.
- achow 7y ago
  Duh. It was right there. But thanks; on doing little bit of search on 'speech diarization' saw that Google Cloud has that service. https://cloud.google.com/speech-to-text/docs/multiple-voices https://cloud.google.com/speech-to-text/docs/multiple-voices And then came across this comparison between various cloud transcription service, which should be helpful for evaluating on diarization aspect as well. AI-POWERED TRANSCRIPTION SERVICES SHOWDOWN: AWS VS. GOOGLE VS. IBM WATSON VS. NUANCE https://www.armedia.com/blog/transcription-services-aws-google-ibm-nuance/ https://www.armedia.com/blog/transcription-services-aws-goog...

by achow 7y ago

gregsadetsky 7y ago

Transcribe does “Recognize Multiple Speakers” — it’s on the page that you linked to, in the list of features. I would also recommend comparing it to Google’s and maybe MS/Azure’s services. Aside from the fidelity of the transcription itself, and the accuracy of disambiguating the different speakers, I’m also not convinced that all of these services will give you an end timestamp (start timestamps are sometimes there, but not necessarily for every word or sentence). You could try a multi prong approach by doing the transcript to get text and speakers only (using the services mentioned above), and then using an aligner such as “gentle” [0] to find the start / end times. You will have some gaps and wrongly transcribed words, but it may be a start..! [0] https://github.com/lowerquality/gentle https://github.com/lowerquality/gentle

yorwba 7y ago

From your link: Recognize Multiple Speakers Amazon Transcribe is able to recognize when the speaker changes and attribute the transcribed text appropriately. This can significantly reduce the amount of work needed to transcribe audio with multiple speakers like telephone calls, meetings, and television shows. So they claim to be able to do it. However, having to do speaker diarization doesn't exactly make speech recognition easier, so you should adjust your expectations regarding the error rate accordingly.

achow 7y ago
Duh. It was right there. But thanks; on doing little bit of search on 'speech diarization' saw that Google Cloud has that service. https://cloud.google.com/speech-to-text/docs/multiple-voices https://cloud.google.com/speech-to-text/docs/multiple-voices And then came across this comparison between various cloud transcription service, which should be helpful for evaluating on diarization aspect as well. AI-POWERED TRANSCRIPTION SERVICES SHOWDOWN: AWS VS. GOOGLE VS. IBM WATSON VS. NUANCE https://www.armedia.com/blog/transcription-services-aws-google-ibm-nuance/ https://www.armedia.com/blog/transcription-services-aws-goog...