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---
license: other
tags:
- text-to-speech
- neural-vocoder
- diffusion probabilistic model
inference: false
datasets:
- LJSpeech
language:
- English
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This model is open access and available to all, with a license further specifying rights and usage.
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
- **Developed by:** Robin Rombach, Patrick Esser
- **Model type:** Diffusion-based text-to-speech generation model
- **Language(s):** English
- **License:**
- **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}
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*This model card was written based on the [DALL-E Mini model card](https://huggingface.co/dalle-mini/dalle-mini).* |