基于联合损失函数的语音质量特征增强分析
Speech Quality Feature Enhancement Analysis Based on Joint Loss Function
杨玲玲1
作者信息
- 1. 河南工业贸易职业学院 信息工程学院,河南 郑州 450064
- 折叠
摘要
为确保代价函数能够根据人耳感知特点开展分析过程,设计了一种联合损失函数的语音增强深度学习算法;针对损失函数计算过程加入关于人耳听觉的数据.研究结果表明:本文设计的混合损失函数实现了增强语音质量的明显优化.以常规损失函数MES进行处理时,增强语音发生了明显失真;以联合损失函数进行处理时,可以明显降低增强语音失真程度,获得更优的语音质量.
Abstract
In order to ensure that the cost function can carry out the analysis process according to the character-istics of human ear perception,a speech enhancement deep learning algorithm combined with loss function is de-signed on the basis of the above.The auditory data of human ear are added to the calculation process of loss func-tion.The results show that the hybrid loss function designed in this paper can achieve obvious optimization of en-hanced speech quality.When the conventional loss function MES is used,the enhanced speech is obviously distort-ed.When processing with joint loss function,the degree of enhanced speech distortion can be significantly reduced and better speech quality can be obtained.
关键词
语音增强/联合损失函数/听觉/语音失真Key words
speech enhancement/joint loss function/hearing/distortion of speech引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据