Spectral Subband Centroids as Complementary Features for Speaker Authentication

  • Norman Poh Hoon Thian
  • Conrad Sanderson
  • Samy Bengio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3072)


Most conventional features used in speaker authentication are based on estimation of spectral envelopes in one way or another, e.g., Mel-scale Filterbank Cepstrum Coefficients (MFCCs), Linear-scale Filterbank Cepstrum Coefficients (LFCCs) and Relative Spectral Perceptual Linear Prediction (RASTA-PLP). In this study, Spectral Subband Centroids (SSCs) are examined. These features are the centroid frequency in each subband. They have properties similar to formant frequencies but are limited to a given subband. Empirical experiments carried out on the NIST2001 database using SSCs, MFCCs, LFCCs and their combinations by concatenation suggest that SSCs are somewhat more robust compared to conventional MFCC and LFCC features as well as being partially complementary.


Linear Discriminant Analysis Speech Recognition Gaussian Mixture Model Automatic Speech Recognition Speech Recognition System 
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

  • Norman Poh Hoon Thian
    • 1
  • Conrad Sanderson
    • 1
  • Samy Bengio
    • 1
  1. 1.IDIAPMartignySwitzerland

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