ABSTRACT Sign language is a form of communication used by persons with disabilities who are deaf to communicate through movement. Every movement in sign language has a meaning that not everyone can understand. To be able to translate the meaning of each movement needed a pattern recognition method. The method used in designing this application is Hidden Markov Models. In designing this application using a Leap Motion camera that functions as a sensor to capture the movement of the skeleton in the hand. The sign language movement that is translated is SIBI sign language consisting of 5 words namely "Brother", "Sister", "Eat", "Patience" and "I". Based on the results of testing and analysis shows that the system as a whole has not been able to recognize movement well, with success reaching around 20%. This is because there are still errors in the learning process.
Copyrights © 2020