一种新的对数能量谱熵语音端点检测方法  

A New Voice Activity Detection Using Logarithmic Energy Spectral Entropy

作　　者：赵欢[1] 王纲金[1] 赵丽霞[1] 

机构地区：[1]湖南大学计算机与通信学院,湖南长沙410082

出　　处：《湖南大学学报（自然科学版）》2010年第7期72-77,共6页Journal of Hunan University:Natural Sciences

基　　金：湖南省科技计划资助项目(05FJ3046);湖南省科技计划重点资助项目(2007GK2015)

摘　　要：将一种新的对数能量(LE)特征和谱熵(SE)特征相结合,提出一种新的对数能量谱熵(LESE)特征,采用模糊C均值聚类算法和贝叶斯信息准则算法进行LESE特征门限估计,并使用双门限法进行语音端点检测.在TIMIT连续语音库上的实验结果表明,相比于能量谱熵(EE)法和对数能量(LE)法,在噪声环境下LESE法具有更好的检测性能,表现出更好的稳健性.当信噪比为-5 dB时,LESE法的检测错误率仅为18.02%,在信噪比为0～10 dB时,其检测错误率要明显低于EE法和LE法.Logarithmic Energy（LE） and Spectral Entropy（SE） were integrated to form a new characteristic,Logarithmic Energy Spectral Entropy（LESE）,by using Fuzzy C Means Clustering algorithm and Bayesian Information Criterion algorithm to estimate the thresholds of the LESE characteristic,and by using dual threshold method for voice activity detection.Experiments on the TIMIT continuous speech database have shown that,compared with the Energy spectral Entropy（EE） and LE in the noisy environments,the LESE has better performance not only in detection but also in robustness.When the SNR is-5 dB,the detection error rate of the LESE is only 18.02%,and while the SNR is 0～10 dB,its detection error rate is significantly lower than the EE and LE.

关 键 词：语音处理 语音端点检测 对数能量谱熵 能量谱熵 对数能量 

分 类 号：TP391.42[自动化与计算机技术—计算机应用技术] TN912.34[自动化与计算机技术—计算机科学与技术]