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MVNet: Memory Assistance and Vocal Reinforcement Network for Speech Enhancement

2022-09-15 13:57:48
Jianrong Wang, Xiaomin Li, Xuewei Li, Mei Yu, Qiang Fang, Li Liu
arXiv_SD
           
Abstract

Speech enhancement improves speech quality and promotes the performance of various downstream tasks. However, most current speech enhancement work was mainly devoted to improving the performance of downstream automatic speech recognition (ASR), only a relatively small amount of work focused on the automatic speaker verification (ASV) task. In this work, we propose a MVNet consisted of a memory assistance module which improves the performance of downstream ASR and a vocal reinforcement module which boosts the performance of ASV. In addition, we design a new loss function to improve speaker vocal similarity. Experimental results on the Libri2mix dataset show that our method outperforms baseline methods in several metrics, including speech quality, intelligibility, and speaker vocal similarity et al.

Abstract (translated)

URL

https://arxiv.org/abs/2209.07302

PDF

https://arxiv.org/pdf/2209.07302.pdf

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