Speaker Recognition Using a Binary Representation and Specificities Models

  • Gabriel Hernández-Sierra
  • Jean-François Bonastre
  • José Ramón Calvo de Lara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)


State of the Art speaker recognition methods are mainly based on GMM/UBM based supervector paradigm. Recently, a simple representation of speech based on local binary decision taken on each acoustic frame have been proposed, allowing to represent a speech excerpt as a binary matrix. This article is based on a similar approach. A new temporal block representation of the binary transformed data as well as three simple algorithms to obtain an efficient similarity measure are proposed. The experimental results show a better robustness of the proposed approach and a similar or better overall performance over classical approaches.


speaker recognition binary values accumulative vector 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gabriel Hernández-Sierra
    • 1
    • 2
  • Jean-François Bonastre
    • 2
  • José Ramón Calvo de Lara
    • 1
  1. 1.Advanced Technologies Application CenterHavanaCuba
  2. 2.LIAUniversity of AvignonFrance

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