Genetic algorithm application to the standard Arabic phonemes classification

The goal of this article is the application of genetic algorithms (GAs) to the automatic speech recognition (ASR) domain at the acoustic sequences classification level. Speech recognition has been cast as a pattern classification problem where we would like to classify an input acoustic signal into one of all possible phonemes. Also, the supervised classification has been formulated as a function optimization problem. Thus, we have attempted to recognize Standard Arabic (SA) phonemes of continuous, naturally spoken speech by using GAs, which have several advantages in resolving complicated optimization problems. In SA there are 40 sounds. We have analyzed a corpus that contains several sentences composed of the whole SA phoneme types in the initial, medium, and final positions, recorded by several male speakers.