Noisy speech pitch detection based on mathematical morphology and weighted MACF

  • Authors:

  • Xia Wang;Hongmei Tang;Xiaoqun Zhao

  • Affiliations:

  • School of Information Engineering, Hebei University of Technology, Tianjin, China;School of Information Engineering, Hebei University of Technology, Tianjin, China;School of Electronic Information and Engineering, Tongji University, Shanghai, China

  • Venue:
  • SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
  • Year:
  • 2004

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Abstract

In speech processing, pitch period is a very important characteristic parameter, but accurate pitch is not easy to be detected, especially in noisy environments, because speech signal is nonstationary and quasiperiodical This paper describes a new method based upon mathematical morphology and weighted modified autocorrelation function(MACF) Morphology is a nonlinear method which is based on set-theoretical algebra, we can form kinds of morphology filters using different structuring elements Weighted MACF modifies traditional autocorrelation method with reciprocal of AMDF Experiments show that the combination of these algorithms provides robust performance and makes better result in noisy speech pitch detection.