Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge
Audio and Speech Processing
2023-03-15 v1 Sound
Abstract
In ICASSP 2023 speech signal improvement challenge, we developed a dual-stage neural model which improves speech signal quality induced by different distortions in a stage-wise divide-and-conquer fashion. Specifically, in the first stage, the speech improvement network focuses on recovering the missing components of the spectrum, while in the second stage, our model aims to further suppress noise, reverberation, and artifacts introduced by the first-stage model. Achieving 0.446 in the final score and 0.517 in the P.835 score, our system ranks 4th in the non-real-time track.
Keywords
Cite
@article{arxiv.2303.07621,
title = {Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge},
author = {Mingshuai Liu and Shubo Lv and Zihan Zhang and Runduo Han and Xiang Hao and Xianjun Xia and Li Chen and Yijian Xiao and Lei Xie},
journal= {arXiv preprint arXiv:2303.07621},
year = {2023}
}
Comments
Accepted by ICASSP 2023