magicse / hifigan-denoiser

HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks

HiFiGAN Denoiser

This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks.

Citations

@misc{su2020hifigan,
      title={HiFi-GAN: High-Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks}, 
      author={Jiaqi Su and Zeyu Jin and Adam Finkelstein},
      year={2020},
      eprint={2006.05694},
      archivePrefix={arXiv},
      primaryClass={eess.AS}
}

Requirement

Tested on Python 3.6

pip install -r requirements.txt

Train & Tensorboard

• python train.py -c [config yaml file]

• tensorboard --logdir log_dir

Inference

• python inference.py -p [checkpoint path] -i [input wav path]

Checkpoint :

• WIP

References

• HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks
• Denoising Wavenet Generator
• StarGAN VC Discriminator
• Melgan Multi-Scale Discriminator
• Parallel Wavegan
• HiFi GAN vocoder's MSD and multi-gpu training code