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A Speaker Recognition System Based on an Auditory Model and Neural Nets: Performance at Different Levels of Sound Pressure and of Gaussian White Noise

  • Ernesto A. Martínez–Rams
  • Vicente Garcerán–Hernández
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6687)

Abstract

This paper performs the assessment of an auditory model based on a human nonlinear cochlear filter-bank and on Neural Nets. The efficiency of this system in speaker recognition tasks has been tested at different levels of voice pressure and different levels of noise. The auditory model yields five psychophysical parameters with which a neural network is trained. We used a number of Spanish words from the ’Ahumada’ database as uttered by native male speakers.

Keywords

Hair Cell Speaker Recognition Speaker Modeling Inner Hair Cell Auditory Model 
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 2011

Authors and Affiliations

  • Ernesto A. Martínez–Rams
    • 1
  • Vicente Garcerán–Hernández
    • 2
  1. 1.Universidad de OrienteSantiago de CubaCuba
  2. 2.Universidad Politécnica de CartagenaCartagena, MurciaEspaña

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