In this article, the authors deal with the machine translation of written English text to sign language. They study the existing systems and issues in order to propose an implantation of a statistical machine translation from written English text to American Sign Language (English/ASL) taking care of several features of sign language.

During ICTA Conference, I presented a paper entitled “How Could Robots Improve Social Skills in Children with Autism?” which is a position paper that aims to improve educational skills of autistic children. The paper was presented with the presence of my colleague Mursi Seraj. Mursi is gifted children having 16 years old who developed the embedded software in Nao Robot.

I am happy to report that on March 10, 2017, I had my doctoral dissertation defense, as part of the WebSign project, and that the committee found my research to be worthy. My dissertation was titled “Machine Translation for Sign Language based on Statistical Approach” and was based on translation between American Sign Language and English written text, as well as new transcription system for Sign Language based on Gloss Annotation System was proposed.

Recent years have witnessed an increasing interest in the mobile computing realm. Gartner says that mobile device (smartphones and tablets) sales are on a continuous rise from year to year, and the future of enterprise applications, both for enterprise workers and consumers, is mobility. Actually, multiple platforms are making mobile devices’ markets at a global scale for all consumers all over the word.

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 synthesized through a 3D avatar for interpretation. First, we translate the input text to gloss, a written form of ASL. Second, we pass the output to the WebSign Plug-in 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.