QwenAudio/SenseVoice

Health v2 · maintenance only

Adoption not part of the score

9386 stars · 829 forks observed · 2026-09-26

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SenseVoice is an open-source speech foundation model (SenseVoiceSmall) providing multilingual ASR, spoken language identification, speech emotion recognition, and audio event detection for Mandarin, Cantonese, English, Japanese, and Korean. It uses a non-autoregressive end-to-end framework for low-latency inference and integrates with FunASR for deployment and finetuning.

Use cases

• transcribe speech to text in Mandarin, Cantonese, English, Japanese, or Korean
• detect emotion from speech audio
• identify the spoken language of an audio clip
• detect audio events like applause, laughter, or coughing
• find a fast low-latency alternative to Whisper for speech recognition
• finetune an ASR model on domain-specific audio samples

When to choose

• you need fast, accurate multilingual ASR with extra emotion and audio-event tags
• your target languages are Mandarin, Cantonese, English, Japanese, or Korean
• you want low-latency non-autoregressive inference or easy finetuning via FunASR

When to avoid

• you need speaker diarization as a single-model output (it requires composing separate FunASR VAD and CAM++ pipelines)
• you need ASR for languages beyond the five supported by the released checkpoint
• you need a tiny embedded deployment without GPU or C++/llama.cpp tooling

Facets

library · maturity active

speech-recognition audio-processing machine-learning llm-inference speech-processing machine-learning python cpp cross-platform asr speech-to-text emotion-recognition audio-event-detection language-identification multilingual funasr whisper-alternative transcription cantonese audio natural-language-processing gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="QwenAudio/SenseVoice")