BibTeX
@MISC{Combrink05supervisedby:,
author = {Andries J. Combrink},
title = {Supervised by: Dr. L. van Zijl Declaration},
year = {2005}
}
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Abstract
I, the undersigned, hereby declare that the work contained in this thesis is my own original work and has not previously in its entirety or in part been submitted at any university for a degree. Signature:.................. Date:.................. ii Sign Languages such as South African Sign Language, are proper natural lan-guages; they have their own vocabularies, and they make use of their own gram-mar rules. However, machine translation from a spoken to a signed language creates in-teresting challenges. These problems are caused as a result of the differences in character between spoken and signed languages. Sign Languages are classified as visual-spatial languages: a signer makes use of the space around him, and gives visual clues from body language, facial expressions and sign movements to help him communicate. It is the absence of these elements in the written form of a spoken language that causes the contextual ambiguities during machine transla-tion. The work described in this thesis is aimed at resolving the ambiguities caused by a translation from written English to South African Sign Language. We designed and implemented a preprocessor that uses areas of linguistics such as anaphora resolution and a data structure called a scene graph to help with the spatial aspect of the translation. The preprocessor also makes use of semantic and syntactic analysis, together with the help of a semantic relational database, to find emotional context from text. This analysis is then used to suggest body language, facial expressions and sign movement attributes, helping us to address the visual aspect of the translation. The results show that the system is flexible enough to be used with different types of text, and will overall improve the quality of a machine translation from English into a Sign Language. iii
Keyphrases
van zijl declaration sign language machine translation south african sign language facial expression body language original work data structure proper natural lan-guages contextual ambiguity machine transla-tion visual clue syntactic analysis spatial aspect scene graph spoken language ii sign language gram-mar rule visual aspect hereby declare semantic relational database in-teresting challenge sign movement different type visual-spatial language anaphora resolution emotional context sign movement attribute
