Transcribe Multi-Speaker Meetings Locally with Speaker Diarization using FunASR
Standard local Whisper lumps all speakers into one wall of text. Use Alibaba open-source FunASR (Paraformer + CAM++ speaker diarization) to label Speaker A/B/C offline with high Chinese accuracy.
BEST FOR
Executive assistants, lawyers, consultants, project managers, journalists
REQUIREMENTS
Python or Docker; multi-speaker audio recording
✦ WHY THIS WORKFLOW
For Chinese and code-switched meetings, open-source FunASR (Paraformer + CAM++) offers faster inference, built-in hotword boosting and native speaker diarization out of the box.
Below is a multi-speaker meeting transcript generated by FunASR with `Speaker 1 / Speaker 2 / Speaker 3` labels.
Please:
1) [Infer Roles]: Deduce each speaker name or role from context in the opening exchanges and label them accordingly;
2) [Per-Person Action Matrix]: List each participant commitments, raised blockers and concrete action items with deadlines.
[Transcript]
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