| | |
| | | |
| | | ## Contributors |
| | | |
| | | | <div align="left"><img src="docs/images/damo.png" width="180"/> | <div align="left"><img src="docs/images/nwpu.png" width="260"/> | <img src="docs/images/China_Telecom.png" width="200"/> </div> | <img src="docs/images/RapidAI.png" width="200"/> </div> | <img src="docs/images/DeepScience.png" width="200"/> </div> | |
| | | |:---------------------------------------------------------------:|:---------------------------------------------------------------:|:--------------------------------------------------------------:|:-------------------------------------------------------:|:-----------------------------------------------------------:| |
| | | | <div align="left"><img src="docs/images/damo.png" width="180"/> | <div align="left"><img src="docs/images/nwpu.png" width="260"/> | <img src="docs/images/China_Telecom.png" width="200"/> </div> | <img src="docs/images/RapidAI.png" width="200"/> </div> | <img src="docs/images/DeepScience.png" width="200"/> </div> | <img src="docs/images/aihealthx.png" width="200"/> </div> | |
| | | |:---------------------------------------------------------------:|:---------------------------------------------------------------:|:--------------------------------------------------------------:|:-------------------------------------------------------:|:-----------------------------------------------------------:|:-----------------------------------------------------------:| |
| | | |
| | | ## Acknowledge |
| | | |
| | |
| | | 4. We acknowledge [ChinaTelecom](https://github.com/zhuzizyf/damo-fsmn-vad-infer-httpserver) for contributing the VAD runtime. |
| | | 5. We acknowledge [RapidAI](https://github.com/RapidAI) for contributing the Paraformer and CT_Transformer-punc runtime. |
| | | 6. We acknowledge [DeepScience](https://www.deepscience.cn) for contributing the grpc service. |
| | | 6. We acknowledge [AiHealthx](http://www.aihealthx.com/) for contributing the websocket service and html5. |
| | | |
| | | ## License |
| | | 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. |
| | |
| | | ## Citations |
| | | |
| | | ``` bibtex |
| | | @inproceedings{gao2022paraformer, |
| | | title={Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition}, |
| | | author={Gao, Zhifu and Zhang, Shiliang and McLoughlin, Ian and Yan, Zhijie}, |
| | | @inproceedings{gao2023funasr, |
| | | author={Zhifu Gao and Zerui Li and Jiaming Wang and Haoneng Luo and Xian Shi and Mengzhe Chen and Yabin Li and Lingyun Zuo and Zhihao Du and Zhangyu Xiao and Shiliang Zhang}, |
| | | title={FunASR: A Fundamental End-to-End Speech Recognition Toolkit}, |
| | | year={2023}, |
| | | booktitle={INTERSPEECH}, |
| | | year={2022} |
| | | } |
| | | @inproceedings{gao2020universal, |
| | | title={Universal ASR: Unifying Streaming and Non-Streaming ASR Using a Single Encoder-Decoder Model}, |
| | | author={Gao, Zhifu and Zhang, Shiliang and Lei, Ming and McLoughlin, Ian}, |
| | | booktitle={arXiv preprint arXiv:2010.14099}, |
| | | year={2020} |
| | | } |
| | | @inproceedings{Shi2023AchievingTP, |
| | | title={Achieving Timestamp Prediction While Recognizing with Non-Autoregressive End-to-End ASR Model}, |
| | | author={Xian Shi and Yanni Chen and Shiliang Zhang and Zhijie Yan}, |
| | | booktitle={arXiv preprint arXiv:2301.12343} |
| | | year={2023} |
| | | @inproceedings{gao22b_interspeech, |
| | | author={Zhifu Gao and ShiLiang Zhang and Ian McLoughlin and Zhijie Yan}, |
| | | title={{Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition}}, |
| | | year=2022, |
| | | booktitle={Proc. Interspeech 2022}, |
| | | pages={2063--2067}, |
| | | doi={10.21437/Interspeech.2022-9996} |
| | | } |
| | | ``` |