MOSS Transcribe Diarize 0.9B MOSS Transcribe Diarize 0.9B is an end to end audio understanding model for long form multi speaker transcription, diarization, timestamps, and acoustic event awareness. It supports transcription and diarization across 50+ languages, single pass inference on audio recordings up to 90 minutes long, and custom hotword prompting for domain specific terms. Given an audio or video file, the model generates a compact speaker aware transcript in one pass, including timestamps and anonymous speaker labels such as [S01] , [S02] , and beyond. News 2026 07 22: The subtitle Web UI now supports both Simplified Chinese and English. 2026 07 14: 🏆 MOSS Transcribe Diarize won first place in the 2nd MLC SLM Challenge at INTERSPEECH 2026, spanning 14 languages (English, French, German, Italian, Portuguese, Spanish, Japanese, Korean, Russian, Thai, Vietnamese, Tagalog, Urdu, Turkish). 2026 07 09: Released MOSS Transcribe Diarize 0.9B. Contents Introduction Model Architecture Evaluation Quickstart Environment Setup Python Usage Serve with vLLM and SGLang Subtitle Web App Output Format More Information License Citation Introduction MOSS Transcribe Diarize 0.9B turns real wo…
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