An accurate recognizer for basic Arabic sounds

This paper is part of an ongoing work aiming to build an accurate Arabic sounds recognizer for teaching and learning purposes. Early phases of this work were dedicated to the development of a particular sound database from recitations of the Holy Quran to cover classical Arabic sounds; speech signals of this sound database were manually segmented and labelled on three levels: Word, phoneme, and allophone. Next, two baseline recognizers were built to validate the speech segmentation on both phoneme and allophone levels and also to test the feasibility of the sounds' recognition intended target. This current phase considers the development of an elaborated recognizer, by considering the basic sounds and looking for their distinctive features (e.g. duration, energy, etc.) to determine which ones will be particularly helpful to identify the phonological variation of the basic sound. Here, we present the first results of the basic sounds recognition obtained so far. © 2006-2016 Asian Research Publishing Network (ARPN).