Support of Arabic Sign Language Machine Translation based on Morphological processing | Zendy

Sawsan Asjea | Zendy; Omar Abdul-Jabbar Ismail | Zendy; Souheil Khawatmi | Zendy

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Support of Arabic Sign Language Machine Translation based on Morphological processing

Author(s) -

Sawsan Asjea,

Omar Abdul-Jabbar Ismail,

Souheil Khawatmi

Publication year - 2019

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2019919564

Subject(s) - computer science , arabic , natural language processing , machine translation , translation (biology) , sign (mathematics) , artificial intelligence , sign language , linguistics , chemistry , philosophy , mathematical analysis , biochemistry , mathematics , messenger rna , gene

This paper presents a morphological processing system as a part of arabic text to arabic sign language machine translation system. This morphological processing depends on Farasa analyzer tool, Stanford model and Arramooz lexicon. The characteristics of sign language are achieved to get intermediate arabic sign language sentences. Then these sentences are searched in a sign language dictionary word by word to display the related signs images if available, or to display letters of word using finger spelling alphabet images. The proposed system is tested on many non-vowelized arabic sentences, and good results and high accuracy are obtained.

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