Communication between deaf and hearing children using statistical machine translation

Communication with hearing people society is an important problem for deaf people. Because they are not learned the valid rules of spoken language that hearing people use them. We therefor prepare an efficient corpus and apply it to Moses Machine Translation to simplify these communications. We choose communications between children because they use e-communications more than adults. All of the systems that automatically process sign language corpus rely on appropriate data. So our corpus with a limited set of words and with specific subject is the first Persian corpus containing Persian language, PL, and Persian sign language, PSL, based on the domain of children conversations. At the first step raw data are pre-processed which provides necessary information for translation. These data are statistic information extracted of sentences. After getting important data from initial sentences, the corpus is applied for training of Moses machine translation. Beside on the main goal of this system, we can educate deaf people the valid Persian grammar that is a problem for deaf people in school and society. In this paper we compare our results with the results taken from Moses decoder in other spoken languages that indicate our purpose is applicable in real world.