- Paper Title: Toward Degradation-Robust Voice Conversion
- Authors: Chien-yu Huang*, Kai-Wei Chang*, Hung-yi Lee
- Paper Link: https://arxiv.org/abs/2110.07537
To appear in the proceedings of ICASSP 2022, equal contribution from first two authors
Both Speech Enhancement Concatenation and End-to-End Denoising Training can effectively imporve state-of-the-art VC models' degradation robustness and adversarial robustness.
- Pros: Any-off-the-shelf model applies.
- Cons: More computations are required for inference.
- Pros: Combine Voice conversion and speech enhancement in a single model.
- Cons: Need more resouces for training.
https://cyhuang-tw.github.io/robust-vc-demo/
@inproceedings{huang2022toward,
title={Toward Degradation-Robust Voice Conversion},
author={Huang, Chien-yu and Chang, Kai-Wei and Lee, Hung-yi},
booktitle={ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={6777--6781},
year={2022},
organization={IEEE}
}