Ability of Evolutionary and Recurrent SOM model GA-RSOM in Phonemic Recognition Optimization

Mohamed Salah Salhi; Najet Arous; Noureddine Ellouze

doi:https://doi.org/10.14445/22315373/IJMTT-V4I6P3

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 4 | Issue 6 | Year 2013 | Article Id. IJMTT-V4I6P3 | DOI : https://doi.org/10.14445/22315373/IJMTT-V4I6P3

Ability of Evolutionary and Recurrent SOM model GA-RSOM in Phonemic Recognition Optimization

Mohamed Salah Salhi ,Najet Arous, Noureddine Ellouze

Citation :

Mohamed Salah Salhi ,Najet Arous, Noureddine Ellouze, "Ability of Evolutionary and Recurrent SOM model GA-RSOM in Phonemic Recognition Optimization," International Journal of Mathematics Trends and Technology (IJMTT), vol. 4, no. 6, pp. 97-106, 2013. Crossref, https://doi.org/10.14445/22315373/IJMTT-V4I6P3

Abstract

The phoneme recognition aims to process a speech signal, characterized by a non-linearity with very high dynamics, allowing to perform various tasks on an information processing machine by an operator using orally address. This paper focuses on a proposed strategy, which implements an evolutionary recurrent self organizing map(SOM) model in phonemes recognition to improve their rates. It is a hybrid model (GA-RSOM) reflecting the approaches of K-means mobile centers, the evolutionary genetic algorithm (GA) principle and the recurrent temporal appearance of Kohonen map (RSOM) to be a powerful optimization tool for phonemic recognition, even in adverse environmental conditions.

Keywords

The SOM model; the recurrent SOM; the K-means mobile centers; the genetic Algorithm GA; the hybrid model (GARSOM).

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