首页 | 本学科首页   官方微博 | 高级检索  
     

强噪声环境下改进的语音端点检测算法
引用本文:鲁远耀,周 妮,肖 珂,叶 青.强噪声环境下改进的语音端点检测算法[J].计算机应用,2014,34(5):1386-1390.
作者姓名:鲁远耀  周 妮  肖 珂  叶 青
作者单位:北方工业大学 信息工程学院,北京 100144
基金项目:“十一五”国家科技支撑计划重点项目
摘    要:为了提高强噪声环境下语音端点检测的正确率,克服传统的短时能量和短时过零率双门限语音端点检测算法在低信噪比(SNR)条件下检测性能急剧下降这一缺陷,提出了一种改进的语音端点检测算法。该方法对强噪声环境下的语音信号,首先进行小波阈值去噪,提高信噪比,再采用双门限法进行端点检测。实验结果表明,该算法具有一定的鲁棒性,在强噪声环境下仍能准确地进行语音端点检测,从而该算法的有效性得到验证。

关 键 词:端点检测  小波阈值  去噪  双门限  信噪比
收稿时间:2013-10-21
修稿时间:2013-12-26

Improved speech endpoint detection algorithm in strong noise environment
LU Yuanyao ZHOU Ni.Improved speech endpoint detection algorithm in strong noise environment[J].journal of Computer Applications,2014,34(5):1386-1390.
Authors:LU Yuanyao ZHOU Ni
Affiliation:College of Information Engineering, North China University of Technology, Beijing 100144, China
Abstract:To improve the correctness of speech endpoint detection in strong noise environment, and overcome the disadvantage in traditional dual-threshold speech endpoint detection based on short-time energy and short-time zero-crossing rate, whose performance degrades sharply in low Signal-to-Noise Ratio (SNR) environment, an improved speech endpoint detection algorithm was proposed. In this method, the noisy speech signal was de-noised to enhance SNR at first, then the dual-threshold speech endpoint detection algorithm was used to detect the endpoints of the de-noised speech signal. The experimental results indicate that the proposed method not only has strong robustness, but also can achieve high detection accuracy in strong noise environment, so the effectiveness of the algorithm is proved.
Keywords:
本文献已被 CNKI 等数据库收录!
点击此处可从《计算机应用》浏览原始摘要信息
点击此处可从《计算机应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号