SIGNBRIDGE REALTIME SIGN LANGUAGE INTERPRETATION FOR INCLUSIVE COMMUNICATION

ABSTRACT :-This paper presents Signbridge, a novel system designed for realtime interpretation of sign languageinto spoken and written language, fostering inclusive communication for the deaf and hard-of-hearingcommunity. Signbridge leverages advanced computer vision techniques, including deep learningbasedpose estimation and gesture recognition, to accurately capture and translate sign languagegestures. Furthermore, it incorporates natural language processing (NLP) for contextual understandingand fluency enhancement. The system's realtime capabilities are crucial for seamless communicationin diverse settings, bridging the gap between sign language users and those unfamiliar with it. Weevaluate the system's performance on a custom-collected dataset and demonstrate its potential forimproving accessibility and inclusivity. Keywords: Sign Language, Real-time Interpretation, Machine Learning, Computer Vision,Accessibility, Assistive Technology, Gesture Recognition, Inclusive Communication, Deep Learning,Natural Language Processing.