Feature Request
I'd like to suggest considering FunASR as an ASR option for Offmute, particularly because it provides a complete speech processing pipeline with built-in speaker diarization.
Why this fits Offmute
Offmute handles meeting transcription and diarization. FunASR provides all the components needed in a single toolkit — no need to stitch together separate VAD, ASR, and diarization systems:
- VAD (FSMN-VAD): Robust voice activity detection
- ASR (Paraformer): Fast, accurate speech recognition
- Speaker Diarization (CAM++): State-of-the-art speaker clustering
- Punctuation: Automatic punctuation restoration
- Timestamps: Word-level and sentence-level timing
Key technical advantages
- End-to-end pipeline: All components work together out of the box
- CAM++ diarization: Competitive with pyannote on meeting scenarios
- Fast inference: Non-autoregressive Paraformer is significantly faster than autoregressive models
- Simple API:
pip install funasr — unified interface for the full pipeline
- No API keys: Fully local, aligns with privacy-conscious meeting tools
Integration potential
Could serve as an alternative or complement to the current LLM-based approach, potentially reducing compute requirements while providing structured speaker-attributed transcripts.
Link
Feature Request
I'd like to suggest considering FunASR as an ASR option for Offmute, particularly because it provides a complete speech processing pipeline with built-in speaker diarization.
Why this fits Offmute
Offmute handles meeting transcription and diarization. FunASR provides all the components needed in a single toolkit — no need to stitch together separate VAD, ASR, and diarization systems:
Key technical advantages
pip install funasr— unified interface for the full pipelineIntegration potential
Could serve as an alternative or complement to the current LLM-based approach, potentially reducing compute requirements while providing structured speaker-attributed transcripts.
Link