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

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