Next-Gen Assistive Technology: AI Applications for Deaf-Mute and Blind Communities

In today's interconnected world, communication gaps still exist between individuals with sensory impairments, specifically the blind and deaf-mute communities. This paper introduces BridgeAI, a novel assistive technology platform designed to overcome these communication barriers by leveraging cutting-edge AI technologies. BridgeAI employs Convolutional Neural Networks (CNN) for sign language recognition, speech-to-text, and text-to-speech models tailored for communication between the blind and deaf-mute individuals. The key innovation lies in the use of a custom-built dataset, enhanced through MediaPipe for real-time hand tracking, alongside an integrated Region of Interest (ROI)-based approach to improve gesture recognition accuracy. This study presents the architecture, implementation, and results of BridgeAI, which achieved a sign language recognition accuracy of 96.8%, demonstrating significant potential in improving accessibility for the blind and deaf-mute communities.