Abstract: This paper aims to contribute in modeling and implementation, over a system on chip SoC, of a powerful technique for phonemes recognition in continuous speech. A neural model known by its efficiency in static data recognition, named SOM for self organization map, is developed into a recurrent model to incorporate the temporal aspect in these applications. The obtained model RSOM will subsequently introduced to ensure the diversification of the genetic algorithm GA populations to expand even more the search space and optimize the obtained results. We assigned a chromosomal vision to this model in an effort to improve the information recognition rate.

Mohamed Salah Salhi, Nejib Khalfaoui and Hamid Amiri, “Evolutionary Strategy of Chromosomal RSOM Model on Chip for Phonemes Recognition” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070720

@article{Salhi2016,
title = {Evolutionary Strategy of Chromosomal RSOM Model on Chip for Phonemes Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070720},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070720},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {7},
author = {Mohamed Salah Salhi and Nejib Khalfaoui and Hamid Amiri}
}