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.ipynb_checkpoints/README-checkpoint.md

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+
+# Diff-Pitcher (PyTorch)
+
+Official Pytorch Implementation of [Diff-Pitcher: Diffusion-based Singing Voice Pitch Correction](https://engineering.jhu.edu/lcap/data/uploads/pdfs/waspaa2023_hai.pdf)
+
+--------------------
+
+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](#examples) to use Diff-Pitcher.
+
+--------------------
+
+Diff-Pitcher
+
+- [Demo Page](#demo)
+- [Todo List](#todo)
+- [Code Examples](#examples)
+- [References](#references)
+- [Acknowledgement](#acknowledgement)
+
+## Demo
+
+🎵 Listen to [examples](https://jhu-lcap.github.io/Diff-Pitcher/)
+
+## Todo
+- [x] Update codes and demo
+- [x] Support 🤗 [Diffusers](https://github.com/huggingface/diffusers)
+- [x] Upload checkpoints
+- [x] Pipeline tutorial
+- [ ] Merge to [Your-Stable-Audio](https://github.com/haidog-yaqub/Your-Stable-Audio)
+- [ ] Audio Plugin Support
+## Examples
+- Download checkpoints: 🎒[ckpts](https://github.com/haidog-yaqub/DiffPitcher/tree/main/ckpts)
+- Prepare environment: [requirements.txt](requirements.txt)
+- Feel free to try:
+  - template-based automatic pitch correction: [template_based_apc.py](template_based_apc.py)
+  - score-based automatic pitch correction: [score_based_apc.py](score_based_apc.py)
+
+
+## References
+
+If you find the code useful for your research, please consider citing:
+
+```bibtex
+@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:
+
+```bibtex
+@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}
+}
+```
+```bibtex
+@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)](https://engineering.jhu.edu/lcap/)
+
+We borrow code from following repos:
+
+ - `Diffusion Schedulers` are based on 🤗 [Diffusers](https://github.com/huggingface/diffusers)
+ - `2D UNet` is based on [DiffVC](https://github.com/huawei-noah/Speech-Backbones/tree/main/DiffVC)

README.md

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+<img src="img\cover.jpg">
 
 # Diff-Pitcher (PyTorch)