readme: ---
  license: other
  tags:
  - text-to-speech
  - neural-vocoder
  - diffusion probabilistic model
  inference: false
  datasets: 
  - LJSpeech
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    Any organization or individual is prohibited from using any technology mentioned in this paper to generate someone's speech without his/her consent, including but not limited to government leaders, political figures, and celebrities. If you do not comply with this item, you could be in violation of copyright laws.
  
    
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  ---
  
  # ProDiff and FastDiff Model Card
  
  ## Key Features
    - **Extremely-Fast** diffusion text-to-speech synthesis pipeline for potential **industrial deployment**.
    - **Tutorial and code base** for speech diffusion models.
    - More **supported diffusion mechanism** (e.g., guided diffusion) will be available.
  
  
  ## Model Details
  - **Model type:** Diffusion-based text-to-speech generation model
  - **Language(s):** English
  - **Model Description:** A conditional diffusion probabilistic model capable of generating high fidelity speech efficiently.
  - **Resources for more information:** [FastDiff GitHub Repository](https://github.com/Rongjiehuang/FastDiff), [FastDiff Paper](https://arxiv.org/abs/2204.09934).  [ProDiff GitHub Repository](https://github.com/Rongjiehuang/ProDiff), [ProDiff Paper](https://arxiv.org/abs/2207.06389).
  - **Cite as:**
  
        @inproceedings{huang2022prodiff,
           title={ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech},
           author={Huang, Rongjie and Zhao, Zhou and Liu, Huadai and Liu, Jinglin and Cui, Chenye and Ren, Yi},
           booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
           year={2022}
  
        @inproceedings{huang2022fastdiff,
           title={FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis},
           author={Huang, Rongjie and Lam, Max WY and Wang, Jun and Su, Dan and Yu, Dong and Ren, Yi and Zhao, Zhou},
           booktitle = {Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI-22}},
           year={2022}
  - 
  
  
  *This model card was written based on the [DALL-E Mini model card](https://huggingface.co/dalle-mini/dalle-mini).*