Indonesia Sign Language Letter Interpreter Application using Leap Motion Control based on Naive Bayes Classifier

EasyChair Preprint 599

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 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. 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%

Keyphrases: Indonesian Sign Language Letters, Leap Motion Control, Naïve Bayes

@booklet{EasyChair:599,
  author    = {Ridwang and Syafaruddin and Amil Ahmad Ilham and Ingrid Nurtanio},
  title     = {Indonesia Sign Language Letter Interpreter Application using Leap Motion Control based on Naive Bayes Classifier},
  howpublished = {EasyChair Preprint 599},
  year      = {EasyChair, 2018}}