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基于Fisher線性判別分析的語音信號端點檢測方法

王明合 張二華 唐振民 許昊

王明合, 張二華, 唐振民, 許昊. 基于Fisher線性判別分析的語音信號端點檢測方法[J]. 電子與信息學(xué)報, 2015, 37(6): 1343-1349. doi: 10.11999/JEIT141122
引用本文: 王明合, 張二華, 唐振民, 許昊. 基于Fisher線性判別分析的語音信號端點檢測方法[J]. 電子與信息學(xué)報, 2015, 37(6): 1343-1349. doi: 10.11999/JEIT141122
Wang Ming-he, Zhang Er-hua, Tang Zhen-min, Xu Hao. Voice Activity Detection Based on Fisher Linear Discriminant Analysis[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1343-1349. doi: 10.11999/JEIT141122
Citation: Wang Ming-he, Zhang Er-hua, Tang Zhen-min, Xu Hao. Voice Activity Detection Based on Fisher Linear Discriminant Analysis[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1343-1349. doi: 10.11999/JEIT141122

基于Fisher線性判別分析的語音信號端點檢測方法

doi: 10.11999/JEIT141122

Voice Activity Detection Based on Fisher Linear Discriminant Analysis

  • 摘要: 傳統(tǒng)的語音端點檢測方法對輔音,特別是受到噪聲污染的清音部分與背景噪聲之間分離能力不足。針對上述問題,該文提出一種基于Fisher線性判別分析的梅爾頻率倒譜系數(shù)(F-MFCC)端點檢測方法。將清音信號和背景噪聲視為兩類分類問題,采用Fisher準(zhǔn)則求解具有判別信息的最佳投影方向,使得投影后的特征參數(shù)具有最小類內(nèi)散度和最大類間散度,從而增大清音與背景噪聲的可分離性。在不同語音庫上的實驗結(jié)果表明,F(xiàn)-MFCC能夠在不同信噪比和背景噪聲條件下提高語音端點檢測的準(zhǔn)確率。
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出版歷程
  • 收稿日期:  2014-08-29
  • 修回日期:  2014-12-19
  • 刊出日期:  2015-06-19

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