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Voice Recognition with Neural Networks, Fuzzy Logic and Genetic Algorithms

  • Patricia Melin
  • Oscar Castillo
Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 172)

Abstract

We describe in this chapter the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case of speaker recognition by analyzing the sound signals with the help of intelligent techniques, such as the neural networks and fuzzy systems. We use the neural networks for analyzing the sound signal of an unknown speaker, and after this first step, a set of type-2 fuzzy rules is used for decision making. We need to use fuzzy logic due to the uncertainty of the decision process. We also use genetic algorithms to optimize the architecture of the neural networks. We illustrate our approach with a sample of sound signals from real speakers in our institution.

Keywords

Hide Markov Model Vocal Tract Sound Signal Speaker Recognition Voice Recognition 
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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Authors and Affiliations

  • Patricia Melin
    • 1
  • Oscar Castillo
    • 2
  1. 1.Department of Computer ScienceTijuana Institute of TechnologyChula VistaUSA
  2. 2.Department of Computer ScienceTijuana Institute of TechnologyChula VistaUSA

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