语音增强算法综述及性能分析  

Review and Performance Analysis of Speech Enhancement Algorithms

作　　者：尹栋[1] 蒋涉权 刘宝光[1] 杨立东[1] 王晶[1] 

机构地区：[1]北京理工大学信息与电子学院,北京100081

出　　处：《电声技术》2015年第5期58-61,65,共5页Audio Engineering

基　　金：国家自然科学基金项目(11161140319);内蒙古自然科学基金项目(2012MS0909);内蒙古高校科研项目(NJZY13139)

摘　　要：语音增强是解决噪声污染的一种有效手段,其主要目标就是从带噪语音中尽可能地提取纯净语音,目前已发展为语音信号处理的一个重要分支,在实际中具有重要价值。实际中经常用到的算法主要有谱减法、维纳滤波、基于统计模型的增强算法(如MMSE)和子空间法。主要介绍谱减法、MMSE、两步消噪(TSNR)和子空间法的算法基本原理,并采用客观评价指标对四种典型算法的降噪效果进行比较和分析。Speech enhancement is an effective method to solve noise pollution, the main target is to extract pure voice from the noisy speech as much as possible, and it has been an important research field in speech processing and has an important value in practice. Actually, the mainly often used algorithms include Spectral Subtraction, Wiener Filter, the algorithms based on statistical model （e. g. MMSE） and Subspace Decomposition. This paper mainly discusses the basic principles of spectral subtraction, MMSE, two -step noise reduction （TSNR） and subspace decomposition and also makes comparisons and analysis on the performance of noise reduction among the four algorithms by using objective assessment index.

关 键 词：语音增强 谱减法 TSNR MMSE 子空间 

分 类 号：TN912.3[电子电信—通信与信息系统]