现代信息科技2024，Vol.8Issue(14)：64-68,5.DOI:10.19850/j.cnki.2096-4706.2024.14.013
基于自注意力机制改进的SEGAN语音增强
Improved SEGAN Speech Enhancement Based on Self-Attention Mechanism
田子晗 1张涵 1周培勇1
作者信息
- 1. 新疆大学 计算机科学与技术学院,新疆 乌鲁木齐 830017
- 折叠
摘要
Abstract
Speech enhancement improves speech quality and understandability by suppressing background noise,thus improving the performance of speech related products.Aiming at the problem that SEGAN model lacks global key information in the process of speech signal processing,this paper proposes an improved generate adversarial network voice enhancement algorithm based on Self-Attention Mechanism:SA-SEGAN.SA-SEGAN uses the Self-Attention Mechanism to process the output of the encoder to extract the important global information of the space and channel of interest,so as to process the voice signal more perfectly.It also uses Log-Cosh loss to better process samples with larger deviation,and introduces Quantile Loss to endow the model with the ability to explore the distribution of samples.Experiments show that SA-SEGAN is 10.9%higher than SEGAN in terms of perceptual evaluation.And the ablation experiment confirms that the three methods used in the experiment play an active role.关键词
语音增强/自注意力机制/智能语音处理/深度学习Key words
speech enhancement/Self-Attention Mechanism/intelligent speech processing/Deep Learning分类
信息技术与安全科学引用本文复制引用
田子晗,张涵,周培勇..基于自注意力机制改进的SEGAN语音增强[J].现代信息科技,2024,8(14):64-68,5.
