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A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan
10.5120/ijca2016907799

Shereen A Mohamed, Mohamed A Abdou and Y F Hassan. Article: A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation. International Journal of Computer Applications 133(5):5-9, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Shereen A. Mohamed and Mohamed A. Abdou and Y. F. Hassan},
	title = {Article: A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {5},
	pages = {5-9},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Cascaded machine translation systems are essential for Deaf people. Speech recognizers and sign language translators when combined together constitute helpful automatic machine translators. This paper introduces an automatic translator from Arabic spoken language into Arabic sign language. This system aims to integrate Deaf students into classrooms of hearing ones. The proposed system consists of three cascaded modules: a modified Arabic speech recognizer that works using adaptation, an Arabic machine translator, and a developed signing avatar animator. The system is evaluated on real case studies and shows good performance.

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Keywords

Arabic Sign Language (ArSL), Deaf students, Example-based translation system, signing avatars