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Speaker Identification Using Higher Order Spectral Phase Features and their Effectiveness vis–a–vis Mel-Cepstral Features

  • Vinod Chandran
  • Daryl Ning
  • Sridha Sridharan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3072)

Abstract

The effectiveness of higher-order spectral (HOS) phase features in speaker recognition is investigated by comparison with Mel Cepstral features on the same speech data. HOS phase features retain phase information from the Fourier spectrum unlike Mel–frequency Cepstral coefficients (MFCC). Gaussian mixture models are constructed from Mel–Cepstral features and HOS features, respectively, for the same data from various speakers in the Switchboard telephone Speech Corpus. Feature clusters, model parameters and classification performance are analyzed. HOS phase features on their own provide a correct identification rate of about 97% on the chosen subset of the corpus. This is the same level of accuracy as provided by MFCCs. Cluster plots and model parameters are compared to show that HOS phase features can provide complementary information to better discriminate between speakers.

Keywords

Gaussian Mixture Model Speaker Recognition Speaker Model High Order Spectrum Cepstral Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Vinod Chandran
    • 1
  • Daryl Ning
    • 1
  • Sridha Sridharan
    • 1
  1. 1.Queensland University of TechnologyBrisbaneAustralia

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