Arabic text to Arabic sign language example-based translation system
This dissertation presents the first corpus-based system for translation from Arabic text into Arabic Sign Language (ArSL) for the deaf and hearing impaired, for whom it can facilitate access to conventional media and allow communication with hearing people. In addition to the familiar technical problems of text-to-text machine translation,building a system for sign language translation requires overcoming some additional challenges. First,the lack of a standard writing system requires the building of a parallel text-to-sign language corpus from scratch, as well as computational tools to prepare this parallel corpus. Further, the corpus must facilitate output in visual form, which is clearly far more difficult than producing textual output. The time and effort involved in building such a parallel corpus of text and visual signs from scratch mean that we will inevitably be working with quite small corpora. We have constructed two parallel Arabic text-to-ArSL corpora for our system. The first was built from school level language instruction material and contains 203 signed sentences and 710 signs. The second was constructed from a children's story and contains 813 signed sentences and 2,478 signs. Working with
Almohimeed, Abdulaziz
QA75 Electronic computers. Computer science
Arabic text to Arabic sign language example-based translation system. This dissertation presents the first corpus-based system for translation from Arabic text into Arabic Sign Language (ArSL) for the deaf and hearing impaired, for whom it can facilitate access to conventional media and allow communication with hearing people. In addition to the familiar technical problems of text-to-text machine translation,building a system for sign language translation requires overcoming some additional challenges. First,the lack of a standard writing system requires the building of a parallel text-to-sign language corpus from scratch, as well as computational tools to prepare this parallel corpus. Further, the corpus must facilitate output in visual form, which is clearly far more difficult than producing textual output. The time and effort involved in building such a parallel corpus of text and visual signs from scratch mean that we will inevitably be working with quite small corpora. We have constructed two parallel Arabic text-to-ArSL corpora for our system. The first was built from school level language instruction material and contains 203 signed sentences and 710 signs. The second was constructed from a children's story and contains 813 signed sentences and 2,478 signs. Working with
arabic_text arabic sign_language example based translation system present first corpus_based system translation_arabic text arabic sign_language deaf hearing impaired facilitate access conventional medium allow communication hearing people addition familiar technical problem text text machine_translation building system sign_language translation require overcome additional challenge first lack standard write_system require build parallel text sign_language corpus scratch well computational tool prepare parallel_corpus corpus must facilitate output visual_form clearly far difficult produce textual output time effort involve building parallel_corpus text visual sign scratch mean inevitably work quite small corpus construct parallel arabic_text corpus system first build school level language instruction material contain sign sentence sign second constructed child story contain sign sentence sign working