Diff-Pitcher (PyTorch)
Official Pytorch Implementation of Diff-Pitcher: Diffusion-based Singing Voice Pitch Correction
Thank you all for your interest in this research project. I am currently optimizing the model's performance and computation efficiency. I plan to release a user-friendly version, either a GUI or a VST, in the first half of this year, and will update the open-source license.
If you are familiar with PyTorch, you can follow Code Examples to use Diff-Pitcher.
Diff-Pitcher
Demo
🎵 Listen to examples
Todo
- Update codes and demo
- Support 🤗 Diffusers
- Upload checkpoints
- Pipeline tutorial
- Merge to Your-Stable-Audio
- Audio Plugin Support
Examples
- Download checkpoints: 🎒ckpts
- Prepare environment: requirements.txt
- Feel free to try:
- template-based automatic pitch correction: template_based_apc.py
- score-based automatic pitch correction: score_based_apc.py
References
If you find the code useful for your research, please consider citing:
@inproceedings{hai2023diff,
title={Diff-Pitcher: Diffusion-Based Singing Voice Pitch Correction},
author={Hai, Jiarui and Elhilali, Mounya},
booktitle={2023 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)},
pages={1--5},
year={2023},
organization={IEEE}
}
This repo is inspired by:
@article{popov2021diffusion,
title={Diffusion-based voice conversion with fast maximum likelihood sampling scheme},
author={Popov, Vadim and Vovk, Ivan and Gogoryan, Vladimir and Sadekova, Tasnima and Kudinov, Mikhail and Wei, Jiansheng},
journal={arXiv preprint arXiv:2109.13821},
year={2021}
}
@inproceedings{liu2022diffsinger,
title={Diffsinger: Singing voice synthesis via shallow diffusion mechanism},
author={Liu, Jinglin and Li, Chengxi and Ren, Yi and Chen, Feiyang and Zhao, Zhou},
booktitle={Proceedings of the AAAI conference on artificial intelligence},
volume={36},
number={10},
pages={11020--11028},
year={2022}
}
Acknowledgement
Welcome to LCAP! < LCAP (jhu.edu)
We borrow code from following repos: