Unofficial PyTorch implementation of MelGAN vocoder (training in progress)
Tested on Python 3.6
pip install -r requirements.txt- Download dataset for training. This can be any wav files with sample rate 22050Hz. (i.e. LJSpeech was used in paper)
- preprocess:
python preprocess.py -c config/default.yaml -d [data's root path] - Edit configuration
yamlfile
python trainer.py -c [config yaml file] -n [name of the run]tensorboard --logdir logs/
coming soon
coming soon
- Seungwon Park @ MINDsLab Inc. (yyyyy@snu.ac.kr, swpark@mindslab.ai)
- Myunchul Joe @ MINDsLab Inc.
- Rishikesh @ DeepSync Technologies Pvt Ltd.
BSD 3-Clause License.
- utils/stft.py by Prem Seetharaman (BSD 3-Clause License)
- datasets/mel2samp.py from https://github.com/NVIDIA/waveglow (BSD 3-Clause License)
- utils/hparams.py from https://github.com/HarryVolek/PyTorch_Speaker_Verification (No License specified)
- How to Train a GAN? Tips and tricks to make GANs work by Soumith Chintala
- jaywalnut310/MelGAN-Pytorch by Jaehyeon Kim