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arXiv · 2303.07621

Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge

Mingshuai Liu·Shubo Lv·Zihan Zhang·Runduo Han·Xiang Hao·Xianjun Xia·Li Chen·Yijian Xiao·Lei Xie
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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.

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Mingshuai Liu, Shubo Lv, Zihan Zhang, Runduo Han, Xiang Hao, Xianjun Xia, Li Chen, Yijian Xiao, Lei Xie. 2023-03-14. Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge. https://arxiv.org/abs/2303.07621

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