No 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.