|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 133 - Number 5
|Year of Publication: 2016
|Authors: Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan
Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan . A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation. International Journal of Computer Applications. 133, 5 ( January 2016), 5-9. DOI=10.5120/ijca2016907799
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.