期刊文献+

基于分频带自相关函数的混叠语音基频分离提取新算法 被引量:1

Pitch Extracting New Method for Mixed Speeches Based on Multi-band Autocorrelation Function
在线阅读 下载PDF
导出
摘要 混叠语音的基频分离提取问题是听觉场景分析系统的重要一环。以往的分频带自相关函数的混叠语音基频分离提取方法都是基于频带只受混叠信号之一支配的假设,而事实上,频带常常同时受两个信号影响,为此,本文提出了一种混叠语音基频分离提取新算法,算法在寻找可能的频带组时采用了闭环自适应频带选取模块,根据频带组的基频及其周期度确定两个潜在基频,提高了搜索潜在基频的鲁棒性;利用两个潜在基频重新判断频带的归属来分离信号提取基频,提高了提取基频的精度。实验结果证明新算法具有较高的有效基频提取精度。 Extracting pitches from mixed speech is an important part in auditory scene analysis. The former mixed speech pitch extracting method using multi-band autocorrelation function is based on the assumption that frequency channel is dominated by one of the mixed signal, but actually, frequency channel is often dominated by both of the two signals. This paper presents a new bitch extraction method, which uses close-loop adaptive frequencies picking block to pick out the possible frequencies group, selects the two potential pitches base on the frequencies groups pitches and the relation between their periodicity so as to improve the robustness of finding potential pitches. By separating all the frequency channels according to the two potential pitches, the accuracy of the extracted pitch is improved. Experiments show that the new method has higher pitch accuracy than former method.
出处 《信号处理》 CSCD 2004年第5期490-493,共4页 Journal of Signal Processing
基金 国家自然科学基金资助课题(69871011 60172048)
关键词 混叠语音 基频 分频 频带 听觉场景分析 自相关函数 信号 新算法 鲁棒性 搜索 autocorrelation function multi-band pitch
  • 相关文献

参考文献6

  • 1Bergman A.S. Auditory Scene Analysis: The Perceptual Organization of Sound. The MIT Press, 1990.
  • 2Cooke M, Ellis D P W. The auditory organization of speech and other sources in listeners and computational models. Speech Communication, 2001, 35(3-4): 141-177.
  • 3Me~ddis R, O'Mard L. PsychophysicaUy Faithful Methods for Extracting Pitch. In Computational Auditory Scene Analysis (eds: D.Rosenthal & H. Okuno). Lawrence Erlbaum, 1998: 43-58.
  • 4赵鹤鸣,舒春燕,周旭东.基于SHS的重叠语音基音分离检测方法[J].信号处理,2000,16(1):63-67. 被引量:4
  • 5L.R. Rabiner and R.W. Schafer, Digital Processing of Speech Signals, Englewood Cliffs, NJ: Prentice-Hall.1987.
  • 6Meddis R, Hewitt M J. V'muM pitch and phase sensitivity of a computer model of the auditory periphery I: Pitch identification. J. Acoust. Soc. Am., 1991, 89(6): 2866-2882.

二级参考文献6

  • 1汪军,何振亚.瞬时混叠信号盲分离[J].电子学报,1997,25(4):1-5. 被引量:11
  • 2周旭东 赵鹤鸣.基于谐波搜索和跟踪的基音提取方法.1997中国神经计算科学会议论文集[M].,1997.725-728.
  • 3周旭东,1997中国神经计算科学会议论文集,1997年,725页
  • 4杨行峻,语音信号数字处理,1995年
  • 5Luo H Y,博士学位论文,1994年
  • 6Yen K C,ICASSP 97,859页

共引文献3

同被引文献73

  • 1赵鹤鸣,葛良,陈雪勤,俞一彪.基于声音定位和听觉掩蔽效应的语音分离研究[J].电子学报,2005,33(1):158-160. 被引量:16
  • 2汪军,何振亚.瞬时混叠信号盲分离[J].电子学报,1997,25(4):1-5. 被引量:11
  • 3Bregman A S. Auditory scene analysis: the perceptual organization of sound[M]. Cambridge, MA: The MIT Press, 1990.
  • 4Brown G J, Cooke M. Computational auditory scene analysis[J]. Computer Speech and Language, 1994, (8): 297- 336.
  • 5Common P. Independent component analysis, a new concept[J]. Signal Processing, 1994, (36): 287-314.
  • 6ffers M. T. M. Sifting vowels: auditory pitch analysis sound segregation[D]. University of Gronigen, 1983.
  • 7Weintraub M. A theory and computational model of auditory monaural sound separation[D]. E. E, Department, Stanford University, 1985.
  • 8Mellinger D K. Event formation and separation in musical soundeD]. CCRMA, Stanford, 1991.
  • 9Meddis R, Hewitt M. J. Modeling the identification of co ncurrent vowels with different fundamental frequencies [J]. Acoustic Society of America, 1991, 89 (6): 2866- 2882.
  • 10Cooke M P. Modeling auditory processing and organization[D]. CS Dept, Univ. of Sheffield, 1991.

引证文献1

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部