STATIC SIGN LANGUAGE TRANSLATOR USING HAND GESTURE AND SPEECH RECOGNITION

Communication between ordinary and deaf people often has issues because ordinary people lack knowledge of sign language. This research aims to help ordinary people communicate with hearing impaired (deaf) people using sign language. This research aims to produce an Android-based mobile app that can translate static sign language using hand movements into text and also convert the spoken voice into sign language using speech recognition. The framework in this research for hand gesture detection uses the MediaPipe software program. This framework allows the creation of apps that translate hand movements into text that help ordinary people understand sign language. Speech recognition in this research uses the Android speech library. This research succeeded in detecting static letters of the alphabet from the a-z and numbers 0-9. Tests of 540 hand gestures carried out in the morning, afternoon, evening, and night had an average detection time of 4.37 seconds. The fastest object detection times were in the morning at a distance of 30 cm with an average detection time of 2.5 seconds. Based on acceptance testing, 83.13% of the features in this static sign language translator have met the users ’users’ needs when communicating with the deaf using sign language.