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| | | [//]: # (<div align="left"><img src="docs/images/funasr_logo.jpg" width="400"/></div>) |
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| | | ([简体中文](./README_zh.md)|English) |
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| | | # FunASR: A Fundamental End-to-End Speech Recognition Toolkit |
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| | | <p align="left"> |
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| | | <a href=""><img src="https://img.shields.io/badge/OS-Linux%2C%20Win%2C%20Mac-brightgreen.svg"></a> |
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| | | [**News**](https://github.com/alibaba-damo-academy/FunASR#whats-new) |
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| | | | [**Highlights**](#highlights) |
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| | | | [**Installation**](#installation) |
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| | | | [**Usage**](#usage) |
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| | | | [**Papers**](https://github.com/alibaba-damo-academy/FunASR#citations) |
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| | | | [**Runtime**](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime) |
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| | | | [**Model Zoo**](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md) |
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| | | | [**Quick Start**](#quick-start) |
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| | | | [**Runtime**](./funasr/runtime/readme.md) |
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| | | | [**Model Zoo**](./docs/model_zoo/modelscope_models.md) |
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| | | | [**Contact**](#contact) |
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| | | | [**M2MET2.0 Challenge**](https://github.com/alibaba-damo-academy/FunASR#multi-channel-multi-party-meeting-transcription-20-m2met20-challenge) |
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| | | <a name="whats-new"></a> |
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| | | ## What's new: |
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| | | ### FunASR runtime-SDK |
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| | | - 2023.07.03: |
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| | | We have release the FunASR runtime-SDK-0.1.0, file transcription service (Mandarin) is now supported ([ZH](funasr/runtime/readme_cn.md)/[EN](funasr/runtime/readme.md)) |
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| | | ### Multi-Channel Multi-Party Meeting Transcription 2.0 (M2MeT2.0) Challenge |
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| | | We are pleased to announce that the M2MeT2.0 challenge has been accepted by the ASRU 2023 challenge special session. The registration is now open. The baseline system is conducted on FunASR and is provided as a receipe of AliMeeting corpus. For more details you can see the guidence of M2MET2.0 ([CN](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)/[EN](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)). |
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| | | |
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| | | ### Release notes |
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| | | For the release notes, please ref to [news](https://github.com/alibaba-damo-academy/FunASR/releases) |
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| | | <a name="highlights"></a> |
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| | | ## Highlights |
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| | | - FunASR is a fundamental speech recognition toolkit that offers a variety of features, including speech recognition (ASR), Voice Activity Detection (VAD), Punctuation Restoration, Language Models, Speaker Verification, Speaker diarization and multi-talker ASR. |
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| | | - We have released a vast collection of academic and industrial pretrained models on the [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), which can be accessed through our [Model Zoo](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md). The representative [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) model has achieved SOTA performance in many speech recognition tasks. |
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| | | - FunASR offers a user-friendly pipeline for fine-tuning pretrained models from the [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition). Additionally, the optimized dataloader in FunASR enables faster training speeds for large-scale datasets. This feature enhances the efficiency of the speech recognition process for researchers and practitioners. |
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| | | <a name="Installation"></a> |
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| | | ## Installation |
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| | | |
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| | | Install from pip |
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| | | ```shell |
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| | | pip install -U funasr |
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| | | pip3 install -U funasr |
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| | | # For the users in China, you could install with the command: |
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| | | # pip install -U funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple |
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| | | # pip3 install -U funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple |
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| | | ``` |
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| | | Or install from source code |
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| | | For more details, please ref to [installation](https://alibaba-damo-academy.github.io/FunASR/en/installation/installation.html) |
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| | | |
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| | | ## Usage |
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| | | <a name="quick-start"></a> |
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| | | ## Quick Start |
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| | | You could use FunASR by: |
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| | | ### runtime |
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| | | An example with websocket: |
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| | | For the server: |
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| | | ```shell |
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| | | python wss_srv_asr.py --port 10095 |
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| | | cd funasr/runtime/python/websocket |
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| | | python funasr_wss_server.py --port 10095 |
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| | | ``` |
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| | | For the client: |
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| | | ```shell |
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| | | python wss_client_asr.py --host "0.0.0.0" --port 10095 --mode 2pass --chunk_size "5,10,5" |
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| | | #python wss_client_asr.py --host "0.0.0.0" --port 10095 --mode 2pass --chunk_size "8,8,4" --audio_in "./data/wav.scp" --output_dir "./results" |
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| | | python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "5,10,5" |
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| | | #python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "8,8,4" --audio_in "./data/wav.scp" --output_dir "./results" |
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| | | ``` |
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| | | More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/runtime/websocket_python.html#id2) |
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| | | <a name="contact"></a> |
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| | | ## Contact |
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| | | If you have any questions about FunASR, please contact us by |
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