Overview
- Contents and results will be presented with help of an up-and-running ASR system
- Examines Arabic phonology, using an HHM-based classifier
- Uses phonological rules to overcome what is known as the cross-word problem
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)
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About this book
Cross-Word Modeling for Arabic Speech Recognition utilizes phonological rules in order to model the cross-word problem, a merging of adjacent words in speech caused by continuous speech, to enhance the performance of continuous speech recognition systems. The author aims to provide an understanding of the cross-word problem and how it can be avoided, specifically focusing on Arabic phonology using an HHM-based classifier.
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Keywords
Table of contents (6 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Cross-Word Modeling for Arabic Speech Recognition
Authors: Dia AbuZeina, Moustafa Elshafei
Series Title: SpringerBriefs in Speech Technology
DOI: https://doi.org/10.1007/978-1-4614-1213-7
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Dia AbuZeina 2012
Softcover ISBN: 978-1-4614-1212-0Published: 24 November 2011
eBook ISBN: 978-1-4614-1213-7Published: 25 November 2011
Series ISSN: 2191-737X
Series E-ISSN: 2191-7388
Edition Number: 1
Number of Pages: X, 74
Number of Illustrations: 14 b/w illustrations, 1 illustrations in colour
Topics: Signal, Image and Speech Processing, Natural Language Processing (NLP), Computational Linguistics, Communications Engineering, Networks, User Interfaces and Human Computer Interaction, Arabic