Statistical Sign Language Machine Translation: from English written text to American Sign Language Gloss
This works aims to design a statistical machine translation from English text to American Sign Language (ASL). The system is based on Moses tool with some modifications and the results are shown through a 3D avatar from interpretation. As a first step, we translate the input text to gloss, a written form of ASL. Then, we pass the output to the WebSign Plugin to play the sign. Contributions of this work are the use of a new couple of language English/ASL and an improvement of statistical machine translation based on string matching thanks to Jaro distance.
Keywords: Sign Language Processing, Machine Translation, Jaro Distance, Natural Language Processing
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ABOUT THE AUTHORS
Achraf Othman
Achraf Othman is currently a PhD student under the supervision of Prof. Mohamed Jemni. He received in August 2010 the Master degree on Computer Science from Tunis College of Sciences and Techniques (ESSTT), University of Tunis in Tunisia. His research interests are in the areas of Sign Language Processing. His current topics of interests include Grid Computing, Computer graphics and Accessibility of ICT to Persons with Disabilities.
Mohamed Jemni
Mohamed Jemni is a Professor of ICT and Educational Technologies at the University of Tunis, Tunisia. He is the Head of the Laboratory Research of Technologies of Information and Communication (UTIC). Since August 2008, he is the General chair of the Computing Center El Khawarizmi, the internet services provider for the sector of the higher education and scientific research. His Research Projects Involvement are tools and environments of e-learning, Accessibility of ICT to Persons with Disabilities and Parallel & Grid Computing.
Achraf Othman
Achraf Othman is currently a PhD student under the supervision of Prof. Mohamed Jemni. He received in August 2010 the Master degree on Computer Science from Tunis College of Sciences and Techniques (ESSTT), University of Tunis in Tunisia. His research interests are in the areas of Sign Language Processing. His current topics of interests include Grid Computing, Computer graphics and Accessibility of ICT to Persons with Disabilities.
Mohamed Jemni
Mohamed Jemni is a Professor of ICT and Educational Technologies at the University of Tunis, Tunisia. He is the Head of the Laboratory Research of Technologies of Information and Communication (UTIC). Since August 2008, he is the General chair of the Computing Center El Khawarizmi, the internet services provider for the sector of the higher education and scientific research. His Research Projects Involvement are tools and environments of e-learning, Accessibility of ICT to Persons with Disabilities and Parallel & Grid Computing.