AI – Based Two Way Sign Language Communication

Communication between hearing-impaired and hearing individuals remains a persistent global challenge, primarily due to the limited understanding of sign language among the general population. This communication gap frequently leads to social exclusion, dependency on human interpreters, and significant difficulties in critical environments such as healthcare, education, and public services. To address this, the current study proposes an innovative Artificial Intelligence (AI)-based real-time sign language recognition and communication support system. Designed to enable inclusive, two-way interaction, the system utilizes advanced computer vision techniques to capture and preprocess hand gestures. Machine learning models, specifically Convolutional Neural Networks (CNNs), interpret these gestures to generate corresponding text and speech output. Conversely, speech input from hearing users is converted into text and animated visual sign representations to ensure seamless bidirectional communication. Furthermore, the application integrates an SOS emergency alert module and an interactive learning interface for basic sign language. By reducing the dependency on human translators and facilitating natural interaction, this proposed system aims to significantly enhance accessibility, user independence, and social inclusion for the hearing-impaired community.