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| | | # FunASR: A Fundamental End-to-End Speech Recognition Toolkit |
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| | | <strong>FunASR</strong> hopes to build a bridge between academic research and industrial applications on speech recognition. By supporting the training & finetuning of the industrial-grade speech recognition model released on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), researchers and developers can conduct research and production of speech recognition models more conveniently, and promote the development of speech recognition ecology. ASR for Fun！[Model Zoo](docs/modelscope_models.md) |
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| | | <strong>FunASR</strong> hopes to build a bridge between academic research and industrial applications on speech recognition. By supporting the training & finetuning of the industrial-grade speech recognition model released on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), researchers and developers can conduct research and production of speech recognition models more conveniently, and promote the development of speech recognition ecology. ASR for Fun！ |
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| | | ## Release Notes: |
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| | | ### 2023.1.16, funasr-0.1.6 |
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| | | pip install --editable ./ |
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| | | ``` |
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| | | ## Usage |
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| | | For users who are new to FunASR and ModelScope, please refer to [FunASR Docs](https://alibaba-damo-academy.github.io/FunASR/index.html). |
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| | | ## Contact |
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| | | If you have any questions about FunASR, please contact us by |
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| | | - email: [funasr@list.alibaba-inc.com](funasr@list.alibaba-inc.com) |
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| | | - Dingding group and Wechat group: |
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| | | <div align="left"><img src="docs/images/dingding.jpg" width="250"/> <img src="docs/images/wechat.png" width="222"/></div> |
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| | | |Dingding group | Wechat group| |
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| | | |:---:|:---:| |
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| | | |<div align="left"><img src="docs/images/dingding.jpg" width="250"/> |<img src="docs/images/wechat.png" width="222"/></div>| |
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| | | |
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| | | ## Contributors |
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| | | | <div align="left"><img src="docs/images/DeepScience.png" width="250"/> | |
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| | | |:---:| |
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| | | ## Acknowledge |
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| | | 1. We borrowed a lot of code from [Kaldi](http://kaldi-asr.org/) for data preparation. |
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| | | 2. We borrowed a lot of code from [ESPnet](https://github.com/espnet/espnet). FunASR follows up the training and finetuning pipelines of ESPnet. |
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| | | 3. We referred [Wenet](https://github.com/wenet-e2e/wenet) for building dataloader for large scale data training. |
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| | | 4. We acknowledge [DeepScience](https://www.deepscience.cn) for contributing the grpc service. |
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| | | ## License |
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| | | This project is licensed under the [The MIT License](https://opensource.org/licenses/MIT). FunASR also contains various third-party components and some code modified from other repos under other open source licenses. |
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