Multi-Sign Language Glove based Hand Talking System

Abstract

Abstract Many people around the world suffer from losing the ability to talk and hear with different levels of disabilities, caused by either a car or a work accident or some diseases. After losing communication, these people cannot do normal functions of normal life. Along with the aforementioned disabilities, those people may also have psychological effects. This paper introduces a technique to realize multiple sign language translation using a sensors-based glove and an Android smartphone for speech impaired people to communicate normally with people. The design of the hand talking system (HTS) was implemented with a minimum possible number of sensors and a capable sewing controller (Lilypad). The proposed HTS includes flex sensors, Arduino, smartphone, and accelerometer. The HTS uses an Android application programmed to store multi-language in the SQLite database and enables the user to interact with the system. The system provides talking with a letter formed words, or using the most frequently used words in daily communication by hand gesture. The HTS has achieved high accuracy obtained for American Sign Language and Arabic Sing Language which are about 98.26% and 99.33% respectively with an average accuracy of 98.795 for both Sign Languages.