Study on Speech Endpoint Detection Algorithm Based on Wavelet Energy Entropy

被引：0
|
作者：
Yali Cao [1 ]
Jing Gao [1 ]
Guang Yang [1 ]
机构：
[1] Northeastern Univ Qinhuangdao, Qinhuangdao 066004, Peoples R China
来源：
PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC) | 2016年
关键词：
endpoint detection; wavelet transforms; energy entropy; the adaptive band-partition;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper describes a high quality voice activity detection using wavelet energy entropy. In this algorithm, the partitioning of the speech band into sub-bands is performed via a bank of the adaptive band-partitioning filters whose coefficients are derived from a wavelet tree structure. The adaptive band-partitioning models have been proposed to perform endpoint detections of isolated digit utterances spoken in the Language. We use the wavelet energy entropy to analyze each sub-band of speech signal. The results of the proposed algorithm on adaptive band-partitioning of signals and noise regions show a good performance of this method.
引用
收藏
页码：3965 / 3969
页数：5
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