Publication: SIGNMT: An alternative sign-text MT for language learning
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Issued Date
2013-12-01
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ISSN
09226389
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2-s2.0-84894540283
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Mahidol University
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SCOPUS
Bibliographic Citation
Frontiers in Artificial Intelligence and Applications. Vol.253, (2013), 65-82
Suggested Citation
Nadh Ditcharoen, Kanlaya Naruedomkul, Nick Cercone SIGNMT: An alternative sign-text MT for language learning. Frontiers in Artificial Intelligence and Applications. Vol.253, (2013), 65-82. doi:10.3233/978-1-61499-258-5-65 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/31605
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Title
SIGNMT: An alternative sign-text MT for language learning
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Abstract
We present the SIGNMT, Thai Sign to Thai machine translation system, which is able to translate from Thai sign language into Thai text. In the translation process, SIGNMT takes into account the differences between Thai and Thai sign language in terms of both syntax and semantic to ensure the accuracy of translation. SIGNMT was designed to be not only an automatic interpreter but also a language learning tool. It provides the meaning of each word in both text and image forms which is easy to understand for the deaf. The grammar information and the order of the sentence are presented in order to help the deaf in learning Thai, their second language. SIGNMT was designed to support individual learning. With SIGNMT, deaf students are less dependent on a teacher, have more freedom to experiment with their own language and improve their knowledge and learning skills. The SIGNMT system was tested and evaluated in terms of translation accuracy and user satisfaction. The evaluation results show that the translation accuracy is acceptable and it satisfies the users' needs. © 2013 The authors and IOS Press. All rights reserved.