STstavros·Aug 9, 2024
> iirc whisper-diarization uses whisperx under the hood.
It seems like it does:
https://github.com/MahmoudAshraf97/whisper-diarization/blob/...
In OTranscribe: A free and open tool for transcribing audio interviewsMahmoudAshraf97
whisper-diarization
Jupyter Notebook2023–2024
MahmoudAshraf97 / whisper-diarization
whisper-diarization
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
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9Mentions
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5.7KGitHub stars
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What it is
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
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This week on Hacker News
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HN mentions by month9 dated mentions
Observed mentions: 2023-07-21 11:01:46 UTC to 2024-08-09 11:35:08 UTC.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Jul 2023 | 2023-07-01 00:00:00 UTC | 2023-08-01 00:00:00 UTC | 1 | 0 | 1 |
| Aug 2023 | 2023-08-01 00:00:00 UTC | 2023-09-01 00:00:00 UTC | 1 | 0 | 1 |
| Sep 2023 | 2023-09-01 00:00:00 UTC | 2023-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2023 | 2023-10-01 00:00:00 UTC | 2023-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2023 | 2023-11-01 00:00:00 UTC | 2023-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2024 | 2024-01-01 00:00:00 UTC | 2024-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2024 | 2024-02-01 00:00:00 UTC | 2024-03-01 00:00:00 UTC | 1 | 0 | 1 |
| Mar 2024 | 2024-03-01 00:00:00 UTC | 2024-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2024 | 2024-04-01 00:00:00 UTC | 2024-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2024 | 2024-05-01 00:00:00 UTC | 2024-06-01 00:00:00 UTC | 2 | 0 | 2 |
| Jun 2024 | 2024-06-01 00:00:00 UTC | 2024-07-01 00:00:00 UTC | 2 | 1 | 1 |
| Jul 2024 | 2024-07-01 00:00:00 UTC | 2024-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2024 | 2024-08-01 00:00:00 UTC | 2024-09-01 00:00:00 UTC | 2 | 0 | 2 |
What Hacker News says
9 sourcesI needed to do this this week (transcribe an interview with multiple speakers) and used https://github.com/MahmoudAshraf97/whisper-diarization
Worked excellent.
It generates both a file that just contains a line per uninterrupted speaker speech prefixed with the speaker number, as well as a file with timestamps which I believe would be used as subtitles.
In OTranscribe: A free and open tool for transcribing audio interviewsI have a pet ML project that I am doing for fun. I am trying to build a custom transcription and diarizer model for a friend's podcast[1]. My initial solution involved a straight forward implementation using Whisper medium for transcription, and Nemo for diarizing, based on [1]. The results are not bad generally, but since my application involves a fixed set of five known speakers, I thought surely I could fine tune the nemo (or pyannote) diarizer model on their voices to improve accuracy.
Audio samples are easily obtained from their podcast, but manual data labeling is painful for a hobby activity. Further, from what I understand, the real difficulty in performant diarizer models is not speaker recognition generally, but specifically speaker recognition while there is overlapping speech between multiple speakers. I am not even sure how t
Read the rest
o best implement a labeling procedure for segments with overlapping speech.
I started to wonder whether I might bootstrap a decent sample by leveraging TTS vocal cloning models to simulate the five speakers in dialogues with overlapping speech segments. So I ask HN, is this hopelessly naive, or potentially useful technique? Also, any other advice?
[1] https://www.3d6downtheline.com/ [2] https://github.com/MahmoudAshraf97/whisper-diarization/
Ask HN: Using Voice Cloning and TTS to Fine-Tune Diarizer
I have a pet ML project that I am doing for fun. I am trying to build a custom transcription and diarizer model for a friend's podcast[1]. My initial solution involved a straight forward implementation using Whisper medium for transcription, and Nemo for diarizing, based on [1]. The results are not bad generally, but since my application involves a fixed set of five known speakers, I thought surely I could fine tune the nemo (or pyannote) diarizer model on their voices to improve accuracy.
Audio samples are easily obtained from their podcast, but manual data labeling is painful for a hobby activity. Further, from what I understand, the real difficulty in performant diarizer models is not speaker recognition generally, but specifically speaker recognition while there is overlapping speech between multiple speakers. I am not even sure how t
Read the rest
o best implement a labeling procedure for segments with overlapping speech.
I started to wonder whether I might bootstrap a decent sample by leveraging TTS vocal cloning models to simulate the five speakers in dialogues with overlapping speech segments. So I ask HN, is this hopelessly naive, or potentially useful technique? Also, any other advice?
[1] https://www.3d6downtheline.com/
[2] https://github.com/MahmoudAshraf97/whisper-diarization/
That doesn't do diarization, unfortunately. Try https://github.com/MahmoudAshraf97/whisper-diarization or something similar instead.
In SignWave: Program to transcribe text, audio files into a sign language animationRe: Diarization, I had decent results with testing this on Colab a while ago:
https://github.com/MahmoudAshraf97/whisper-diarization
I remember having the usual python package hell when NeMo was updated somewhere, but it seems to be decently well maintained so give it a go.
*Edit, I remember reading somewhere that pyannote was a weak link in other repos, that might be why your other tests were not great.
In Self-hosted offline transcription and diarization service with LLM summary"diarization" is your search term. eg. https://github.com/MahmoudAshraf97/whisper-diarization
In Ask HN: Is there a whisper-like speech-to-text that detects the speaker?https://github.com/MahmoudAshraf97/whisper-diarization
This project has been alright for transcribing audio with speaker diarization. A big finicky. The OpenAI model is better than other paid products(Descript, Riverside) so I’m looking forward to trying MacWhisper.
In MacWhisper: Transcribe audio files on your MacThe project page mentions whisper-diarization (speaker recognition) as a user of faster-whisper. I've been in the market for that, definitely going to try it out.
https://github.com/MahmoudAshraf97/whisper-diarization
In Faster Whisper Transcription with CTranslate2