# FunASR

An industrial speech recognition toolkit for training and running offline, streaming and edge automatic speech recognition, voice activity detection, punctuation restoration and speaker diarization models, with OpenAI-compatible and MCP serving.

FunASR is a speech recognition toolkit covering the full pipeline from training to inference: automatic speech recognition, voice activity detection, punctuation restoration, speaker diarization, and emotion and audio-event tagging, for offline, streaming and edge deployment.

Its models include SenseVoiceSmall for file transcription with emotion and event tags across five languages, Fun-ASR-Nano and Fun-ASR-MLT-Nano for LLM-based file transcription in more languages, and a streaming Paraformer checkpoint for chunked live transcription. Models are used through a Python AutoModel API, a GPU-oriented vLLM path, or a streaming SDK and WebSocket service.

FunASR serves models through an OpenAI-compatible API and an MCP server for use from coding agents, and integrates with frameworks such as LangChain, Dify and AutoGen. It is written in Python and installs from PyPI.

Website: https://www.funasr.com