基于自适应子带功率谱熵的语音端点检测算法  

Speech endpoint detection algorithm based on adaptive subband power spectral entropy

作　　者：李金宝[1] 屈百达[1] 徐宝国[1] 周小祥[1] 

机构地区：[1]江南大学通信与控制工程学院,江苏无锡214122

出　　处：《计算机工程与应用》2007年第12期57-58,65,共3页Computer Engineering and Applications

基　　金：国家科技部"十五"攻关项目(No.2001BA204B01-03)。

摘　　要：在语音处理中,鲁棒性端点检测是语音处理最重要的领域之一,首先提出了一种子带功率谱熵(SPSE)的特征参数,然后,该参数结合Wuetal提出的自适应子带方法(ABS);发现了一种新颖的鲁棒特征参数-自适应子带谱熵(ASPSE),它能成功地在不同的背景噪声下检测语音端点。实验结果表明,在不同的噪声环境和信噪比下,ASPSE参数非常有效,而且该算法优于其它算法。In speech processing,robust endpoint detection is one of the most important areas of speech processing.The paper first proposes a feature parameter,called Subband Power Spectral Entropy （SPSE）.This method is combined with the Adaptive Band Selection（ABS） method proposed by Wu et al.Finally,a novel robust feature parameter,Adaptive Subband Power Spectral Entropy （ASPSE）,is presented to successfully detect endpoints in different background noises.Experimental results indicate that the ASPSE parameter is very effective under different noise conditions with several SNRs.Furthermore,the proposed algorithm outperforms other algorithms.

关 键 词：自适应处理 端点检测 子带分析 功率谱熵 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]