基于谐波和能量特征的单声道浊语音分离方法  

Monaural voiced speech separation based on harmonic and energy features

作　　者：赵立恒[1] 汪增福[1,2] 

机构地区：[1]中国科学技术大学自动化系,合肥230027 [2]中国科学院合肥智能机械研究所,合肥230031

出　　处：《声学学报》2012年第2期218-224,共7页Acta Acustica

基　　金：安徽省科技攻关计划(语音专项;11010202192)资助项目

摘　　要：提出了一种基于谐波和能量特征的单声道浊语音分离方法。该方法将浊语音分离问题转化为声音在时频域的分类问题。首先,在已有谐波特征的基础上,引入能量特征。然后,对于谐波特征明显且能量大的时频单元,在分类器训练阶段复制它们的特征。实验结果表明该方法相比之前的方法有更好的信噪比增益。通过引入能量特征和特征复制,改善了浊语音的分离效果。A monaural voiced speech separation approach based on harmonic and energy features is proposed. The method casts voiced speech separation as sound classification problem in time-frequency domain. First, the energy feature is employed to assist harmonic features. Then, the harmonic and energy features of time-frequency units with obvious harmonicity and large energy are replicated in the process of classifier training. Experimental results show that the proposed method obtains better signal-to-noise ratio improvement compared with previous approaches. The voiced speech separation is improved by introducing energy feature and feature replication.

关 键 词：能量特征 语音分离 谐波特征 分离方法 单声道 信噪比增益 分类问题 问题转化 

分 类 号：TN912.3[电子电信—通信与信息系统]