الفهرس 
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Abstract
Machine translation systems for sign languages play a significant role in facilitating the
communication between Deaf and hearing people, especially when signs interpreters are not
available or their services are expensive. Using virtual human signers, to express the signing,
make these systems more acceptable by Deaf and consequently more applicable.
This thesis aims to study, develop, and implement a machine translation system from Arabic
to Arabic Sign Language (ArSL). The developed system accepts the Arabic utterance as
input via a microphone or audio files, and outputs the translation in an animated form by
means of a signing avatar. It tries to help Deaf students attend courses and share materials
with hearing students.
Considering the Arabic Sign Language, many problems arise when developing such
translation systems. First the Arabic Sign Language is a descriptive language; the signer
describes the words to explain the meaning. Different signs may refer to the same word and
different words may be expressed by the same sign. Second the two hands can be used
interchangeably to express the same sign. Third the lack of Arabic Sign Language corpora,
in this work a new corpus is built from scratch. Finally, the lack of linguistics studies on
Arabic Sign Language, which limits the size of the corpus constructed in this work.
The proposed system consists of three main modules: an Arabic speech recognizer, an
Arabic machine translator, and a 3D signing avatar animator. The Arabic speech recognizer
receives the Arabic speech either via a microphone or an audio file and converts it to its
textual form. A speech recognition library is used to adapt an existing language model to the
Arabic phones. The evaluation of this module separately gives an acceptable Word Error
Rate (WER) using a test data set of real Arabic recorded sentences. The Arabic machine
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translator converts the Arabic text to its equivalent in Arabic Sign Language.