SIGN LANGUAGE INTERPRETER

The communication obstacle for individuals with hearing impairments causes severe issues in education and workplaces. This research considers how artificial intelligence (AI), such as computer vision and language models, can be utilized to develop an intelligent sign language interpretation system. This system is able to rapidly translate gestures into text and speech. We surveyed recent progress from 2018 to 2025 in gesture recognition, deep learning, and natural language processing. We have structured the work into four broad categories: sensor-based motion capture, AI-based gesture recognition, text-to-speech translation frameworks, and real-time communication interfaces. Our review emphasizes the strengths and limitations of today’s systems. Accuracy can go up to 95% in laboratory conditions, but real-time applications in ever-changing environments are still not possible. This project envisages a straightforward design that integrates vision-based gesture recognition, predictive AI interpretation, and speech generation to bridge the communication divide smoothly. The research also identifies areas where additional research is required, including support for multiple languages, context-sensitive interpretation, and low-latency real-time execution. This paper hopes to develop an inclusive and smart communication aid for the hearing-impaired community.