Example Based Amharic Text to Ethiopian Sign Language Machine Translation

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Addis Ababa University


Ethiopian sign language (EthSL) is an independent language used by the Ethiopian Deaf society. Sign language is a visual gestural language, used by the Deaf for everyday communication. In most societies sign language is not known, and if known, it is not well understood even by their own family. This in turn makes their communication to be dependent on interpreters even in situations like medical treatment that need privacy. Machine translation for spoken languages is a successful area of research and development. But in case of sign language, especially in case of EthSL it is in its infancy. This is because Sign language research is still a relatively new area when compared to research into spoken languages. In this study an attempt is made to design and implement an example based Amharic Text to Ethiopian Sign Language Machine Translation system by collecting examples. The example data is processed to produce morphologically analyzed Amharic words, word structures and sentence structures in addition to adopting EthSL dictionary. A prototype performing translation based on knowledge acquired from processed example data is thus developed by involving word feature analysis, matching, alignment and recombination phases. The resulting translation output of EthSL sign is displayed as a sequence of video clips. The system is assessed in terms of adequacy and fluency with three groups of evaluators for different categories of texts. The evaluation result shows that finger spellings, numbers and words from the adopted dictionary were adequately understood with a rank of ‘All meaning’ and with ‘Good’ fluency whereas words out of the adopted dictionary were adequately understood with a rank of ‘Most meaning’ with ‘Acceptable’ fluency. In case of sentences ‘Much meaning’ has been adequately understood with ‘Acceptable’ fluency level. The usability of the prototype was ranked as ‘Excellent’ with a ‘Very good’ level of ease of use. Deaf members of the test teams have been aspired with the capability of the prototype for future use and they expressed their willingness to contribute for full deployment of the system.



Ethiopian Sign Language, Sign Language, Example Based Machine Translation