Research on Speaker Recognition Based on Multifractal Spectrum Feature

  • Authors:

  • Yuhuan Zhou;Jinming Wang;Xiongwei Zhang

  • Affiliations:

  • -;-;-

  • Venue:
  • ICCMS '10 Proceedings of the 2010 Second International Conference on Computer Modeling and Simulation - Volume 01
  • Year:
  • 2010

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Abstract

In this paper, a new nonlinear feature extraction method based on the WTMM (wavelet transform modulus-maxima method) is proposed, which can greatly facilitate the extraction of the multifractal spectrum feature (MSF) from speech signals. The MSF combined with traditional linear features can obviously improve the performance of speaker recognition system. Experiment results show that 6-dimensional MSF combined with LPC make recognition accuracy increase 6.4 percentage points, and 6-dimensional MSF combined with MFCC, LPC make recognition accuracy increase 1.6 percentage points and reach 98.8% in short speech (2 seconds) speaker recognition.