#3232nd of 51 in VoiceFor voice, speech and music
sensevoice
Multilingual speech recognition model with emotion and audio-event tags
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- Stars
- 9.6k
- License
- MIT
- Last commit
- Sep 2026
- Last release
- Aug 2026
- Language
- C
Missed the latest GitHub check; these facts may be older.
Overview
SenseVoice is a speech model that does ASR, spoken language ID, speech emotion recognition and audio event detection in one non-autoregressive model. The released SenseVoiceSmall checkpoint covers Mandarin, Cantonese, English, Japanese and Korean. It runs through FunASR in Python, as ONNX or Libtorch exports, as a FastAPI service, or as a GGUF binary on CPU.
Who it is for: Engineers needing self-hosted multilingual ASR with emotion and event tags
Strengths
- One model outputs transcript, language ID, emotion tag and audio-event tag
- README reports over 5x faster than Whisper-Small in its benchmark setup
- Multiple runtimes: FunASR Python, ONNX, Libtorch, FastAPI, and a GGUF binary without Python
- Includes finetuning scripts and a bounded-memory long-audio script that needs no VAD
Weaknesses
- Released checkpoint supports only 5 languages, not the 50+ cited for the research work
- Speaker diarization needs separate FSMN-VAD and CAM++ models; accuracy not validated
- Direct inference limited to 30 seconds; longer audio needs VAD or windowing
- Event detection is weaker than specialized AED models, per the README
What it needs
- GPU optional
- Docker + Compose
- Needs funasr, ffmpeg, FSMN-VAD, CAM++ (diarization only)
- Models: SenseVoiceSmall, ONNX, Libtorch, GGUF
- port 50000
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