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Comparing spectrum estimators in speaker verification under additive noise degradation

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Author

  • C. Hanilci
  • T. Kinnunen
  • R. Saeidi
  • J. Pohjalainen
  • P. Alku
  • F. Ertas
  • J. Sandberg
  • Maria Sandsten

Summary, in English

Different short-term spectrum estimators for speaker verification under additive noise are considered. Conventionally, mel-frequency cepstral coefficients (MFCCs) are computed from discrete Fourier transform (DFT) spectra of windowed speech frames. Recently, linear prediction (LP) and its temporally weighted variants have been substituted as the spectrum analysis method in speech and speaker recognition. In this paper, 12 different short-term spectrum estimation methods are compared for speaker verification under additive noise contamination. Experimental results conducted on NIST 2002 SRE show that the spectrum estimation method has a large effect on recognition performance and stabilized weighted LP (SWLP) and minimum variance distortionless response (MVDR) methods yield approximately 7 % and 8 % relative improvements over the standard DFT method at -10 dB SNR level of factory and babble noises, respectively in terms of equal error rate (EER).

Department/s

Publishing year

2012

Language

English

Pages

4769-4772

Publication/Series

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Probability Theory and Statistics

Keywords

  • speaker verification
  • spectrum estimation

Conference name

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Conference date

2012-03-25 - 2012-03-30

Conference place

Kyoto, Japan

Status

Published

Research group

  • Statistical Signal Processing
  • Statistical Signal Processing Group

ISBN/ISSN/Other

  • ISSN: 1520-6149
  • ISBN: 978-1-4673-0044-5 (online)
  • ISBN: 978-1-4673-0045-2 (print)