Sign Language Recognition System Using Machine Learning

Sign Language Recognition (SLR) systems aim to improve communication between deaf indi-viduals and individuals who d o not know sign language. The system uses computer vision a nd ma-chine learning techniques to recognize hand gestures, i including hand movements, facial expres-sions, and body post ures. Input is received from sensors such as cameras or depth sensors that can capture images or video frames for further processing. Machine learning models such as CNNs and SV Ms translate these descriptions into words or phrases. The sy stem then converts these results into text or speech, enabling effective communication.