中国邮电高校学报(英文) ›› 2007, Vol. 14 ›› Issue (1): 85-89.doi: 1005-8885 (2007) 01-0085-05

• Artificial Intelligence • 上一篇    下一篇

Unvoiced/voiced classification and voiced harmonic parameters estimation using the third-order statistics

YING Na, ZHAO Xiao-hui, DONG Jing   

  1. Communication Engineering College of Hangzhou Dianzi University, Hangzhou 310018, China
  • 收稿日期:2006-03-31 修回日期:1900-01-01 出版日期:2007-03-30
  • 通讯作者: YING Na

Unvoiced/voiced classification and voiced harmonic parameters estimation using the third-order statistics

YING Na, ZHAO Xiao-hui, DONG Jing   

  1. Communication Engineering College of Hangzhou Dianzi University, Hangzhou 310018, China
  • Received:2006-03-31 Revised:1900-01-01 Online:2007-03-30
  • Contact: YING Na

摘要:

Unvoiced/voiced classification of speech is a challenging problem especially under conditions of low signal-to-noise ratio or the non-white-stationary noise environment. To solve this problem, an algorithm for speech classification, and a technique for the estimation of pairwise magnitude frequency in voiced speech are proposed. By using third order spectrum of speech signal to remove noise, in this algorithm the least spectrum difference to get refined pitch and the max harmonic number is given. And this algorithm utilizes spectral envelope to estimate signal-to-noise ratio of speech harmonics. Speech classification, voicing probability, and harmonic parameters of the voiced frame can be obtained. Simulation results indicate that the proposed algorithm, under complicated background noise, especially Gaussian noise, can effectively classify speech in high accuracy for voicing probability and the voiced parameters.

关键词:

unvoiced/voiced;classification,;harmonic;extraction,;the;third-order;cumulant,;sinusoidal;speech;model

Abstract:

Unvoiced/voiced classification of speech is a challenging problem especially under conditions of low signal-to-noise ratio or the non-white-stationary noise environment. To solve this problem, an algorithm for speech classification, and a technique for the estimation of pairwise magnitude frequency in voiced speech are proposed. By using third order spectrum of speech signal to remove noise, in this algorithm the least spectrum difference to get refined pitch and the max harmonic number is given. And this algorithm utilizes spectral envelope to estimate signal-to-noise ratio of speech harmonics. Speech classification, voicing probability, and harmonic parameters of the voiced frame can be obtained. Simulation results indicate that the proposed algorithm, under complicated background noise, especially Gaussian noise, can effectively classify speech in high accuracy for voicing probability and the voiced parameters.

Key words:

unvoiced/voiced classification;harmonic extraction;the third-order cumulant;sinusoidal speech model

中图分类号: