Innovation in Language Learning

This paper considered interesting findings due to increasingly sophisticated role of artificial neural networks (ANNs).  These findings have been recently recognized and adopted  by  interdisciplinary neurological, educational, and linguistic researchers. That adopted research approach has been applied for systematic realistic investigational modeling of an interdisciplinary discipline incorporating neuroscience, education, and cognitive sciences. Accordingly, ANN models vary in relation to the nature of assigned brain functioning to be modeled. For example, as human learning that takes place autonomously according to received stimuli that are realistically simulated through self-organization modeling. This paper adopts the conceptual approach of (ANN) models inspired by functioning of highly specialized biological neurons specified in reading brain based on the organization the brain's structures/substructures. Additionally, in accordance with the prevailing concept of individual intrinsic characterized properties of highly specialized neurons, presented models closely correspond to performance of these neurons for developing reading brain in a significant way. More specifically, introduced models concerned with their important role played in carrying out cognitive brain function' outcomes. The cognitive goal for reading brain is to translate visualized (orthographic word-from) into a spoken voiced word (phonological word-form). In this context herein, the presented work illustrates via ANN simulation results: How ensembles of highly specialized neurons could be dynamically involved in performing the cognitive function of developing reading brain.

Index Terms— Brain Reading Function, Phonological and orthographic processing, Artificial Neural Networks Modeling, and Pattern Recognition.