Indonesian Dynamic Sign Language Recognition for Individuals with Sensory Disabilities using LSTM
Reni Yunita, Erna Budhiarti Nababan, Maya Silvi Lydia · 2024
People with disabilities often face difficulties communicating with the general public, especially regarding sign language. Sign Language Recognition (SLR) is a technology focused on recognizing, interpreting, and translating sign language into text or speech. SLRs can be divided into two types: static and dynamic. This research focuses on dynamic sign language recognition to develop recognition for Indonesian Sign Language, using the Python programming language with libraries such as Mediapipe, cvzone, sklearn, numpy, and the Long Short-Term Memory (LSTM) technique. These findings show the potential of SLR technology in assisting communication for individuals with disabilities in Indonesia. This research significantly contributes to the development of Indonesian Sign Language SLR.