[1]董胡. 低信噪比环境下改进的语音端点检测算法[J].计算机技术与发展,2016,26(03):71-74.
　DONG Hu. Improved Speech Endpoint Detection under Low SNR Environment[J].,2016,26(03):71-74.
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 低信噪比环境下改进的语音端点检测算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年03期
页码:
71-74
栏目:
智能、算法、系统工程
出版日期:
2016-03-10

文章信息/Info

Title:
 Improved Speech Endpoint Detection under Low SNR Environment
文章编号:
1673-629X（2016)03-0071-04
作者:
 董胡
 长沙师范学院 电子与信息工程系
Author(s):
 DONG Hu
关键词:
 ; 多窗谱估计; 改进谱减法; 谱熵; 语音增强; 端点检测
Keywords:
 ; multitaper spectrum estimation; improved spectral subtraction; spectral entropy; speech enhancement;  endpoint detection
分类号:
TN912.35
文献标志码:
A
摘要:
 端点检测在语音识别中具有非常重要的作用，其准确性将直接影响语音识别系统的正确率。为了提高低信噪比环境下语音端点检测的正确率，提出了一种基于多窗谱估计的改进谱减法和能量谱熵的端点检测算法。该算法首先利用多窗谱估计改进谱减法对含噪语音进行去噪以提高语音信号信噪比，接着对去噪后的语音信号使用新的能量谱熵算法进行端点检测。仿真实验结果表明，同常见端点检测算法相比较，该算法在低信噪比环境下具有较好的端点检测正确率且有一定的鲁棒性，证明了该算法的有效性。
Abstract:
 Endpoint detection has a very important role in speech recognition,its accuracy will directly affect the accuracy of speech recog-nition system. In order to improve the accuracy of speech endpoint detection under low SNR environment,an endpoint detection algorithm based on spectral subtraction of multitaper spectrum estimation and spectral entropy is proposed. Firstly,it uses improved spectral subtrac-tion of multitaper spectrum estimation to denoise speech signal in order to improve signal to noise ratio,and then it utilizes energy-entro-py-ratio algorithm to make endpoint detection for speech signal denoised. Simulation experiment results show that compared with com-mon endpoint detection algorithm,this algorithm has good endpoint detection accuracy and certain robustness in low SNR environment. It proves the effectiveness of the proposed algorithm.

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更新日期/Last Update: 2016-06-12