SenseVoice
Multilingual speech understanding toolkit with ASR, emotion recognition, and audio event detection.
GraphCanon updated 3w · GitHub synced 3w · 42 views this month
Decision brief
SenseVoice is ideal for applications needing fast multilingual ASR with emotion recognition and audio event detection in over 50 languages.
Good fit when
- Projects requiring speed, with non-autoregressive models being up to 15 times faster than Whisper
- Environments where multilingual support is crucial, catering more than 50 languages
Avoid when
- Applications needing Python-based implementation since SenseVoice relies on C and PyTorch for its framework
- Scenarios demanding the lowest level of inference latency as it may have higher overhead compared to simpler models
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (2d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No criticals
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/FunAudioLLM/SenseVoiceSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
SenseVoice is a comprehensive multilingual speech understanding software that supports automatic speech recognition (ASR), emotion recognition, and audio event detection in over 50 languages. It offers faster processing speed compared to Whisper while supporting non-autoregressive models.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 30, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 30, 2026
- Languages
- c
Source: github.language · Jul 30, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 30, 2026)
pip install -r requirements.txtSource link
Tags
README
Requirements
pip install -r requirements.txt
SenseVoiceSmall examples and the composed FunASR diarization path require funasr>=1.3.26. If you installed this repository earlier, run pip install -U "funasr>=1.3.26" before retrying the demos.
pip3 install -U funasr funasr-onnx
from pathlib import Path from funasr_onnx import SenseVoiceSmall from funasr_onnx.utils.postprocess_utils import rich_transcription_postprocess
model_dir = "iic/SenseVoiceSmall"
model = SenseVoiceSmall(model_dir, batch_size=10, quantize=True)
Deployment with FastAPI
export SENSEVOICE_DEVICE=cuda:0
fastapi run --port 50000
Requirements
git clone https://github.com/modelscope/FunASR.git && cd FunASR
pip3 install -e ./
🐳 Docker Support
SenseVoice can be built and run using Docker to simplify setup, ensure reproducibility, and support both CPU and GPU inference.
Build with Docker
docker build -t sensevoice .
Docker Compose
Docker Compose provides an easier way to run SenseVoice with persistent model caching, networking etc.
License
- Source code in this repository is licensed under the MIT License.
- Model weights are distributed separately and follow the terms on each model card. The official SenseVoiceSmall model card links to the FunASR Model Open Source License Agreement; other artifacts and conversions may list different terms, so check their model cards before use.
- The maintainers have provided an official SenseVoiceSmall license clarification for the FunASR Model Open Source License Agreement v1.1: Commercial use of the official SenseVoiceSmall weights is permitted when the model license is followed; Section 3 is a responsibility and risk disclaimer rather than an additional non-commercial restriction; and fine-tuned derivative weights may remain private. The Section 2.2 attribution and model-name requirements still apply. This clarification covers the official weights only, so check the terms for third-party conversions and bundled artifacts separately.
For agents
This page has a .md twin and JSON over the API.