Modeling of phonics reading methodology using neural networks

This work addresses a rather challenging and interesting interdisciplinary educational issue. It integrates the analysis and evaluation of natural brain language processing with phonics reading (pronunciation) methodology. Specifically, presented paper concerned with searching for an optimal educational methodology for teaching children “how to read?”. That´s by adopting a simplified neuronal mechanism observed model while human brain speech / pronunciation function is performed. Consequently, the presented modeling of phonics reading methodology adopts the observed behavioral characterizations of brain neural networks. Additionally, mathematical formulation is given considering the suggested reading methodology. Objectively, in order to justify its optimality in teaching children how to read. It´s motivated by a biologically (naturally) inspired artificial neural network (ANN) model considering associative brain function, between two visual and audible signals. Accordingly, the mathematical formulation introduced herein, has been fulfilled realistically via ANN modeling of self-organized learning paradigm, originated from biological basis of Hebbian learning rule.