Machine Translation Approach to Translate Amharic Text to Ethiopian Sign Language

Abstract

Sign language is a communication system using gestures that are interpreted visually. Many people in deaf communities around the world use sign languages as their primary means of communication creating a strong sense of social and cultural identity. About 0.4% of the whole population of Ethiopia is deaf and out of this, more than half is illiterate because of the fact that there are very limited studies conducted on Ethiopian Sign Language. This research document presents a Machine Translation system to translate Amharic text to an equivalent Ethiopian Sign Language (ESL) by finger spelling representation with the help of a 2-dimensional animating avatar rendering the equivalent ESL finger translation. Animating an avatar for rendering Ethiopian finger spelling requires a dynamic and periodic switching of hand shapes and hand movements. Macromedia Flash 8.0 and ActionScript 2.0 are used as a tool to model and design the avatar, the hand shapes and the hand movement definitions. The translation system is tested by 10 deaf people and 66.6% of them responded that the overall performance is good and supportive.