ml-explore / ml-explore/mlx-examples
[Feature Request] Support Speaker Diarization
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- Dominant language
- Python
- Stars
- 9k
- Forks
- 1.2k
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Description
Implement speaker diarization for the existing mlx whisper support to:
- Enhance transcription accuracy in multi-speaker conversations
- Distinguish between different speakers in the output
- Improve overall usability of the transcription feature
This addition will provide more insightful and structured transcripts, making it easier to analyze and understand complex audio content. Thanks
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the existing MLX Whisper support referenced in the issue; no file, test, or entry point is specified. Clarify the diarization approach and expected transcript format before implementation. Done should distinguish speakers in multi-speaker transcripts and preserve the existing transcription behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100