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Support of Arabic Sign Language Machine Translation based on Morphological processing

by Sawsan Asjea, O. Ismail, Souheil Khawatmi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 15
Year of Publication: 2019
Authors: Sawsan Asjea, O. Ismail, Souheil Khawatmi
10.5120/ijca2019919564

Sawsan Asjea, O. Ismail, Souheil Khawatmi . Support of Arabic Sign Language Machine Translation based on Morphological processing. International Journal of Computer Applications. 177, 15 ( Nov 2019), 28-36. DOI=10.5120/ijca2019919564

@article{ 10.5120/ijca2019919564,
author = { Sawsan Asjea, O. Ismail, Souheil Khawatmi },
title = { Support of Arabic Sign Language Machine Translation based on Morphological processing },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2019 },
volume = { 177 },
number = { 15 },
month = { Nov },
year = { 2019 },
issn = { 0975-8887 },
pages = { 28-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number15/30976-2019919564/ },
doi = { 10.5120/ijca2019919564 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:45:59.388667+05:30
%A Sawsan Asjea
%A O. Ismail
%A Souheil Khawatmi
%T Support of Arabic Sign Language Machine Translation based on Morphological processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 15
%P 28-36
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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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Index Terms

Computer Science
Information Sciences

Keywords

Machine Translation (MT) Morphological Analysis Arabic sign language.

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