DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism

This repository is the official PyTorch implementation of our AAAI-2022 paper, in which we propose DiffSinger (for Singing-Voice-Synthesis) and DiffSpeech (for Text-to-Speech).

DiffSinger/DiffSpeech at training	DiffSinger/DiffSpeech at inference

:tada: :tada: :tada: Updates:

Mar.2, 2022: MIDI-new-version: A substantial improvement :sparkles:
Mar.1, 2022: NeuralSVB, for singing voice beautifying, has been released :sparkles: :sparkles: :sparkles: .
Feb.13, 2022: NATSpeech, the improved code framework, which contains the implementations of DiffSpeech and our NeurIPS-2021 work PortaSpeech has been released :sparkles: :sparkles: :sparkles:.
Jan.29, 2022: support MIDI-old-version SVS. :construction: :pick: :hammer_and_wrench:
Jan.13, 2022: support SVS, release PopCS dataset.
Dec.19, 2021: support TTS. HuggingFace🤗 Demo

:rocket: News:

Feb.24, 2022: Our new work, NeuralSVB was accepted by ACL-2022 . Demo Page.
Dec.01, 2021: DiffSinger was accepted by AAAI-2022.
Sep.29, 2021: Our recent work PortaSpeech: Portable and High-Quality Generative Text-to-Speech was accepted by NeurIPS-2021 .
May.06, 2021: We submitted DiffSinger to Arxiv .

Environments

conda create -n your_env_name python=3.8
source activate your_env_name 
pip install -r requirements_2080.txt   (GPU 2080Ti, CUDA 10.2)
or pip install -r requirements_3090.txt   (GPU 3090, CUDA 11.4)

Documents

Tensorboard

tensorboard --logdir_spec exp_name

Audio Demos

Old audio samples can be found in our demo page. Audio samples generated by this repository are listed here:

TTS audio samples

Speech samples (test set of LJSpeech) can be found in resources/demos_1213.

SVS audio samples

Singing samples (test set of PopCS) can be found in resources/demos_0112.

Citation

@article{liu2021diffsinger,
  title={Diffsinger: Singing voice synthesis via shallow diffusion mechanism},
  author={Liu, Jinglin and Li, Chengxi and Ren, Yi and Chen, Feiyang and Liu, Peng and Zhao, Zhou},
  journal={arXiv preprint arXiv:2105.02446},
  volume={2},
  year={2021}}

Acknowledgements

Our codes are based on the following repos:

Also thanks Keon Lee for fast implementation of our work.