A speech endpoint detection algorithm based on entropy and RBF neural network

被引：0
|
作者：
Zhang, Xueying [1 ]
Li, Gaoyun [1 ]
Qiao, Feng [1 ]
机构：
[1] Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Shanxi, Peoples R China
来源：
GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS | 2007年
关键词：
amplitude entropy; neural network; speech endpoint detection; spectral entropy;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Speech endpoint detection is an important step in the field of speech analysis, speech synthesis and speech recognition. This paper proposed an endpoint detection algorithm, which used amplitude entropy, spectral entropy and frame energy as feature parameters and utilized RBF neural network as a feature classification system. 170 sentences are used as testing data to detect speech endpoint, which length is from 4 second to 7 second. The experiments show that the testing results using RBF neural network are better than that using entropy alone or BP neural network based on entropy.
引用
收藏
页码：506 / 509
页数：4
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