Automatic Speech Recognition of Arabic Phonemes with Neural Networks

This book presents a contrastive linguistics study of Arabic and English for the dual purposes of improved language teaching and speech processing of Arabic via spectral analysis and neural networks. Contrastive linguistics is a field of linguistics which aims to compare the linguistic systems of two or more languages in order to ease the tasks of teaching, learning, and translation. The main focus of the present study is to treat the Arabic minimal syllable automatically to facilitate automatic speech processing in Arabic. It represents important reading for language learners and for linguists with an interest in Arabic and computational approaches.

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Mohammed Dib is a Doctor (Maitre de conference A) at the University of Mascara in the English department. He studied at the University of Tlemcen, where he received his license in English, his Magister, and his doctorate in applied linguistics (English-Arabic). His area of interest is contrastive studies in English and Arabic phonetics, phonology, signal processing, speech recognition, and automatic translation. Dr. Dib performed the research for this volume at the Laboratory of Automatic Treatment of the Arabic Language at the University of Tlemcen.

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