MOSS Transcribe Diarize
MOSS Transcribe Diarize is an end to end multimodal large language model that jointly performs speech transcription, speaker diarization, and timestamp prediction. It projects multi speaker acoustic representations into the feature space of a pretrained text LLM, producing time aligned transcripts with speaker labels such as S01 and S02. It supports a 128k context window for inputs up to 90 minutes and handles overlapping multi speaker dialogue across multiple languages.
- Type
- Audio
- Weights
- Open
- Downloads
- 165k
- Likes
- 455
- Pipeline
- audio text to text
- License
- apache-2.0
Model hub
OpenMOSS-Team/MOSS-Transcribe-Diarize
- Repo
- OpenMOSS-Team/MOSS-Transcribe-Diarize
- Library
- transformers
- Access
- Public
Technical tags and languages
Papers
1
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