Speech Enhancement based on DVAE

This repository is the official code for the paper:

Unsupervised Speech Enhancement using Dynamical Variational Auto-Encoders, TASLP, 2022
Xiaoyu Bie, Simon Leglaive, Xavier Alameda-Pineda, Laurent Girin

[Paper]

Dataset

For HumanEva-I and Human3.6M, we follow the instructions in gsps, then put all data into data directory:

• WSJ-QUT (paid): it comes from the the subset of original WSJ dataset, which was used in the CHiME-3 Challenge, corrupted by the QUT noise
• VoiceBank-DEMAND (free): download data from their website, downsample to 16kHz and select p226 & p287 as validation dataset (following MetricGanU)

Train

Test

Bibtex

If you find this code useful, please star the project and consider citing:

@article{bie2022unsupervised,
  title={Unsupervised speech enhancement using dynamical variational autoencoders},
  author={Bie, Xiaoyu and Leglaive, Simon and Alameda-Pineda, Xavier and Girin, Laurent},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  volume={30},
  pages={2993--3007},
  year={2022},
  publisher={IEEE}
}