Towards A Sign Language Gloss Representation Of Modern Standard Arabic
Domain:
natural language processingRecord type:
paperproject
Over 5% of the world's population (466 million people) has disabling hearing
loss. 4 million are children. They can be hard of hearing or deaf. Deaf people
mostly have profound hearing loss. Which implies very little or no hearing.
Over the world, deaf people often communicate using a sign language with
gestures of both hands and facial expressions. The sign language is a
full-fledged natural language with its own grammar and lexicon. Therefore,
there is a need for translation models from and to sign languages. In this
work, we are interested in the translation of Modern Standard Arabic(MSAr) into
sign language. We generated a gloss representation from MSAr that extracts the
features mandatory for the generation of animation signs. Our approach locates
the most pertinent features that maintain the meaning of the input Arabic
sentence.
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