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Speaker Verification in Noisy Environment Using Missing Feature Approach

  • Dayana Ribas
  • Jesús A. Villalba
  • Eduardo Lleida
  • José R. Calvo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6419)

Abstract

In order to handle speech signals corrupted by noise in speaker verification and provide robustness to systems, this paper evaluates the use of missing feature (MF) approach with a novel combination of techniques. A mask estimation based on spectral subtraction is used to determine the reliability of spectral components in a speech signal corrupted by noise. A cluster based reconstruction technique is used to remake the damaged spectrum. The verification performance was evaluated through a speaker verification experiment with signals corrupted by white noise under different signal to noise ratios. The results were promising since they reflected a relevant increase of speaker verification performance, applying MF approach with this combination of techniques.

Keywords

Noisy Environment Equal Error Rate Speaker Recognition Speaker Verification Spectral Subtraction 
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 2010

Authors and Affiliations

  • Dayana Ribas
    • 1
  • Jesús A. Villalba
    • 2
  • Eduardo Lleida
    • 2
  • José R. Calvo
    • 1
  1. 1.Advanced Technologies Application Center (CENATAV)PlayaCuba
  2. 2.Communications Technology Group (GTC), Aragon Institute for Engineering Research (I3A)University of ZaragozaSpain

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