Gesture Based Sign Language Recognition for Specially Challenged Using YOLOv5

Sign language is a vital mode of communication for individuals with hearing and speech impairments, enabling them to interact with the world around them. This paper presents a comprehensive study and implementation of a Gesture-Based Sign Language Recognition system designed to empower specially challenged individuals by providing them with an effective means of communication. The proposed system leverages computer vision,machine learning and deep learning techniques to recognize and interpret gestures, converting them into text or speech. The system has the potential to be integrated into various assistive devices, mobile applications, and educational platforms, making sign language communication more accessible and empowering individuals with hearing and speech impairments.