International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 177 - Issue 15 |
Published: Nov 2019 |
Authors: Sawsan Asjea, O. Ismail, Souheil Khawatmi |
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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 }, year = { 2019 }, volume = { 177 }, number = { 15 }, pages = { 28-36 }, doi = { 10.5120/ijca2019919564 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2019 %A Sawsan Asjea %A O. Ismail %A Souheil Khawatmi %T Support of Arabic Sign Language Machine Translation based on Morphological processing%T %J International Journal of Computer Applications %V 177 %N 15 %P 28-36 %R 10.5120/ijca2019919564 %I Foundation of Computer Science (FCS), NY, USA
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.