Full Description

Responsibility Statement Dia AbuZeina, Moustafa Elshafei
Language Code eng
Edition
Collection Source e-Book BOPTN 2013
Cataloguing Source LibUI eng rda
Content Type text (rdacontent)
Media Type computer (rdamedia)
Carrier Type online resource (rdacarrier)
Physical Description
Link http://link.springer.com/book/10.1007%2F978-1-4614-1213-7
 
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Call Number Barcode Number Availability
e20418404 TERSEDIA
No review available for this collection: 20418404
 Abstract
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.