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README.md
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README.md
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[](https://github.com/Akshay090/svg-banners)
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## 👉🏻 [CosyVoice](https://github.com/FunAudioLLM/CosyVoice) 👈🏻
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## 👉🏻 CosyVoice 👈🏻
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**Fun-CosyVoice 3.0**: [Demos](https://funaudiollm.github.io/cosyvoice3/); [Paper](https://arxiv.org/abs/2505.17589); [Modelscope](https://www.modelscope.cn/studios/FunAudioLLM/Fun-CosyVoice3-0.5B); [CV3-Eval](https://github.com/FunAudioLLM/CV3-Eval)
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**Fun-CosyVoice 3.0**: [Demos](https://funaudiollm.github.io/cosyvoice3/); [Paper](https://arxiv.org/abs/2505.17589); [Modelscope](https://www.modelscope.cn/studios/FunAudioLLM/Fun-CosyVoice3-0.5B); [CV3-Eval](https://github.com/FunAudioLLM/CV3-Eval); [Huggingface](https://huggingface.co/FunAudioLLM/Fun-CosyVoice3-0.5B-2512)
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**CosyVoice 2.0**: [Demos](https://funaudiollm.github.io/cosyvoice2/); [Paper](https://arxiv.org/abs/2412.10117); [Modelscope](https://www.modelscope.cn/studios/iic/CosyVoice2-0.5B); [HuggingFace](https://huggingface.co/spaces/FunAudioLLM/CosyVoice2-0.5B)
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**CosyVoice 2.0**: [Demos](https://funaudiollm.github.io/cosyvoice2/); [Paper](https://arxiv.org/abs/2412.10117); [Modelscope](https://www.modelscope.cn/studios/iic/CosyVoice2-0.5B); [HuggingFace](https://huggingface.co/FunAudioLLM/CosyVoice2-0.5B)
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**CosyVoice 1.0**: [Demos](https://fun-audio-llm.github.io); [Paper](https://funaudiollm.github.io/pdf/CosyVoice_v1.pdf); [Modelscope](https://www.modelscope.cn/studios/iic/CosyVoice-300M)
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### Model download
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We strongly recommend that you download our pretrained `Fun-CosyVoice3-0.5B` `CosyVoice2-0.5B` `CosyVoice-300M` `CosyVoice-300M-SFT` `CosyVoice-300M-Instruct` model and `CosyVoice-ttsfrd` resource.
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``` python
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from modelscope import snapshot_download
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snapshot_download('FunAudioLLM/Fun-CosyVoice3-0.5B-2512', local_dir='pretrained_models/Fun-CosyVoice3-0.5B')
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### Basic Usage
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We strongly recommend using `Fun-CosyVoice3-0.5B` for better performance.
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Follow the code in `example.py` for detailed usage of each model.
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```sh
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python example.py
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``` python
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import sys
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sys.path.append('third_party/Matcha-TTS')
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from cosyvoice.cli.cosyvoice import AutoModel
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import torchaudio
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""" CosyVoice3 Usage, check https://funaudiollm.github.io/cosyvoice3/ for more details
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"""
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cosyvoice = AutoModel(model_dir='pretrained_models/Fun-CosyVoice3-0.5B')
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# zero_shot usage
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for i, j in enumerate(cosyvoice.inference_zero_shot('八百标兵奔北坡，北坡炮兵并排跑，炮兵怕把标兵碰，标兵怕碰炮兵炮。', 'You are a helpful assistant.<|endofprompt|>希望你以后能够做的比我还好呦。',
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'./asset/zero_shot_prompt.wav', stream=False)):
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torchaudio.save('zero_shot_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
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# fine grained control, for supported control, check cosyvoice/tokenizer/tokenizer.py#L280
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for i, j in enumerate(cosyvoice.inference_cross_lingual('You are a helpful assistant.<|endofprompt|>[breath]因为他们那一辈人[breath]在乡里面住的要习惯一点，[breath]邻居都很活络，[breath]嗯，都很熟悉。[breath]',
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'./asset/zero_shot_prompt.wav', stream=False)):
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torchaudio.save('fine_grained_control_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
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# instruct usage, for supported control, check cosyvoice/utils/common.py#L28
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for i, j in enumerate(cosyvoice.inference_instruct2('好少咯，一般系放嗰啲国庆啊，中秋嗰啲可能会咯。', 'You are a helpful assistant. 请用广东话表达。<|endofprompt|>',
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'./asset/zero_shot_prompt.wav', stream=False)):
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torchaudio.save('instruct_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
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for i, j in enumerate(cosyvoice.inference_instruct2('收到好友从远方寄来的生日礼物，那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐，笑容如花儿般绽放。', 'You are a helpful assistant. 请用尽可能快地语速说一句话。<|endofprompt|>',
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'./asset/zero_shot_prompt.wav', stream=False)):
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torchaudio.save('instruct_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
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# hotfix usage
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for i, j in enumerate(cosyvoice.inference_zero_shot('高管也通过电话、短信、微信等方式对报道[j][ǐ]予好评。', 'You are a helpful assistant.<|endofprompt|>希望你以后能够做的比我还好呦。',
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'./asset/zero_shot_prompt.wav', stream=False)):
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torchaudio.save('hotfix_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
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```
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## Discussion & Communication
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You can directly discuss on [Github Issues](https://github.com/FunAudioLLM/CosyVoice/issues).
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You can also scan the QR code to join our official Dingding chat group.
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<img src="./asset/dingding.png" width="250px">
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## Acknowledge
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1. We borrowed a lot of code from [FunASR](https://github.com/modelscope/FunASR).
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2. We borrowed a lot of code from [FunCodec](https://github.com/modelscope/FunCodec).
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3. We borrowed a lot of code from [Matcha-TTS](https://github.com/shivammehta25/Matcha-TTS).
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4. We borrowed a lot of code from [AcademiCodec](https://github.com/yangdongchao/AcademiCodec).
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5. We borrowed a lot of code from [WeNet](https://github.com/wenet-e2e/wenet).
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## Citations
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``` bibtex
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@article{du2024cosyvoice,
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title={Cosyvoice: A scalable multilingual zero-shot text-to-speech synthesizer based on supervised semantic tokens},
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author={Du, Zhihao and Chen, Qian and Zhang, Shiliang and Hu, Kai and Lu, Heng and Yang, Yexin and Hu, Hangrui and Zheng, Siqi and Gu, Yue and Ma, Ziyang and others},
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journal={arXiv preprint arXiv:2407.05407},
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year={2024}
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}
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@article{du2024cosyvoice,
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title={Cosyvoice 2: Scalable streaming speech synthesis with large language models},
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author={Du, Zhihao and Wang, Yuxuan and Chen, Qian and Shi, Xian and Lv, Xiang and Zhao, Tianyu and Gao, Zhifu and Yang, Yexin and Gao, Changfeng and Wang, Hui and others},
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journal={arXiv preprint arXiv:2412.10117},
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year={2024}
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}
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@article{du2025cosyvoice,
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title={CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training},
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author={Du, Zhihao and Gao, Changfeng and Wang, Yuxuan and Yu, Fan and Zhao, Tianyu and Wang, Hao and Lv, Xiang and Wang, Hui and Shi, Xian and An, Keyu and others},
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journal={arXiv preprint arXiv:2505.17589},
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year={2025}
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}
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@inproceedings{lyu2025build,
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title={Build LLM-Based Zero-Shot Streaming TTS System with Cosyvoice},
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author={Lyu, Xiang and Wang, Yuxuan and Zhao, Tianyu and Wang, Hao and Liu, Huadai and Du, Zhihao},
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booktitle={ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
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pages={1--2},
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year={2025},
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organization={IEEE}
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}
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```
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## Disclaimer
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