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

Journal Title: INTERNATIONAL JOURNAL OF MATHEMATICS TRENDS AND TECHNOLOGY - Year 2013, Vol 4, Issue 6

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 (GARSOM) 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.

Authors and Affiliations

Mohamed Salah Salhi ; Najet Arous; Noureddine Ellouze

Keywords

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  • EP ID EP157070
  • DOI -
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How To Cite

Mohamed Salah Salhi ; Najet Arous; Noureddine Ellouze (2013).  Ability of Evolutionary and Recurrent SOM model GA-RSOM in Phonemic Recognition Optimization. INTERNATIONAL JOURNAL OF MATHEMATICS TRENDS AND TECHNOLOGY, 4(6), 97-106. https://europub.co.uk/articles/-A-157070