东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (12): 1690-1693.DOI: -

• 论著 • 上一篇    下一篇

基于短时能零积和鉴别信息的语音端点检测

韩志艳;王旭;王健;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-12-15 发布日期:2013-06-22
  • 通讯作者: Han, Z.-Y.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(50477015)

Speech endpoint detection algorithm based on short-time energy-zero-product and discrimination information

Han, Zhi-Yan (1); Wang, Xu (1); Wang, Jian (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-12-15 Published:2013-06-22
  • Contact: Han, Z.-Y.
  • About author:-
  • Supported by:
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摘要： 为了提高低信噪比下语音端点检测的准确率,提出了一种新型的语音端点检测算法.该算法利用短时能零积法和鉴别信息的互补优势,一边降噪一边端点检测,而且对于被判为噪声的帧利用基于子带能量鉴别信息方法来进行二次复检,根据鉴别信息来更新噪声能量门限,从而能更准确地跟踪噪声的能量变化.实验结果表明,该方法在信噪比变化比较剧烈的情况下仍然能够准确地进行端点检测,对语音信号的后续处理起到了很好的作用.

关键词: 语音信号, 短时能零积, 鉴别信息, 端点检测, 阈值

Abstract: To improve the accuracy of speech endpoint detection in low signal-to-noise ratio(SNR), a new algorithm was proposed. It combines the short-time energy-zero-product with discrimination information, denoising and endpoint detection simultaneously. Then, the frames judged as noisy ones are rechecked via the discrimination information based on the sub-band energy distribution probability to update the noise energy threshold, thus tracking the change for noise energy more accurate. Simulation results showed that the algorithm proposed is able to detect endpoints accurately even if the SNR changes acutely, and it will serve very well the function of subsequent processing of speech signal.

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