metadata

license: other
tags:
  - text-to-speech
  - neural-vocoder
  - diffusion probabilistic model
inference: false
datasets:
  - LJSpeech
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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, FastDiff Paper. ProDiff GitHub Repository, ProDiff Paper.

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.