Indonesian Sign Language Letter Interpreter Application Using Leap Motion Control based on Naïve Bayes Classifier

Abstract

Abstract Most deaf children are born into hearing families and the majority do not begin their Sign Language learning before age 3-6 in school. As children learning Sign Language from infancy show higher language proficiency than those who do not, it underlines the importance of hearing parents learning how to sign. The recent innovation in the technology and introduction of new gesture control based devices, like leap motion controller. Technology that can track finger and hand gestures accurately at very low cost. The research method in Naïve Bayes algorithm, in order to classify 26 alphabet letter of Indonesian sign language including letter J and Z which using gesture for describe it. The Leap Motion controller is a consumer gesture sensor aimed to augment a user’s interactive experience with their computer and it was utilized as an interface for hand motion tracking without the need of wearing any external instruments. It use for derive feature data from the deaf children gesture recording to set data in application. The accuracy level of the test result reached 96%.

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