基于分带谱熵和小波域Teager能量的语音清浊分类算法  

A Speech Voiced/Unvoiced Classification Algorithm Based on the Band-partitioning Spectral Entropy and Teager Energy of Wavelet Transform

作　　者：李如玮[1] 鲍长春[1] 窦慧晶[1] 

机构地区：[1]北京工业大学电子信息与控制工程学院,北京100124

出　　处：《北京工业大学学报》2009年第7期899-903,共5页Journal of Beijing University of Technology

基　　金：北京市教委科技发展计划资助项目(KM200710005001);北京市自然科学基金资助项目(4042009)

摘　　要：基于分带谱熵和小波域Teager能量提出了一种改进的语音清浊分类算法.该算法首先计算频域内的分带谱熵,然后在小波域计算不同频带的Teager能量,计算出低频能量所占的比例,通过这2个参数进行清浊判断.实验结果证明,由于分带谱熵能加深清浊音之间的差异,Teager能量能快速跟踪声门周期内信号能量的变化,因此该算法更容易提取浊音,在纯净语音和含噪语音上的性能都优于幅度能量算法.A improved speech voiced/unvoiced classification algorithm based on the band-partitioning spectral entropy and Teager energy of wavelet transform is proposed in this paper.First,the band-partitioning spectral entropy is computed.Second,the Teager energy of every band of speech decomposed by wavelet transform and the ratio of the energy in the wavelet low-bands to total energy of each speech segment. Finally,the voiced and unvoiced decision is made according to these two parameters.Experimental results show ...

关 键 词：语音分类 小波变换 Teager能量 分带谱熵 

分 类 号：TN912.3[电子电信—通信与信息系统]