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SpringerBriefs in Applied Sciences and Technology

Automatic Speech Recognition of Arabic Phonemes with Neural Networks

A Contrastive Study of Arabic and English

Authors: Dib, Mohammed

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About this book

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.

About the authors

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.

Table of contents (5 chapters)

Table of contents (5 chapters)

Buy this book

eBook n/a
  • ISBN 978-3-319-97710-2
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
Softcover n/a
  • ISBN 978-3-319-97709-6
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Automatic Speech Recognition of Arabic Phonemes with Neural Networks
Book Subtitle
A Contrastive Study of Arabic and English
Authors
Series Title
SpringerBriefs in Applied Sciences and Technology
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
The Author(s), under exclusive licence to Springer Nature Switzerland AG
eBook ISBN
978-3-319-97710-2
DOI
10.1007/978-3-319-97710-2
Softcover ISBN
978-3-319-97709-6
Series ISSN
2191-530X
Edition Number
1
Number of Pages
XIII, 144
Number of Illustrations
4 b/w illustrations, 96 illustrations in colour
Topics