REAL-TIME SIGN LANGUAGE INTERPRETATION IN POLICE INVESTIGATION USING ARTIFICIAL INTELLIGENCE

Information Technology

Communication is the foundation upon which societies are built and relationships flourish. It breaks the barriers of language, culture, and distance, serving as the bedrock for understanding and connection. While spoken language is a primary mode of communication for many, the imperative for inclusive communication becomes profoundly evident when considering individuals who are deaf or hard of hearing. For this community, sign language emerges as a crucial and vibrant means of expression, breaking down barriers and of ering a pathway to understand disabled people’s feelings. Sign language is an expressive mode of communication that relies on visual-gestural elements to convey meaning. Deaf individuals use sign language not only for everyday conversations but also to participate in various aspects of life, including education, work, and social interactions. This project aims to enhance communication and accessibility in police investigations by implementing a real-time sign language interpretation system using artificial intelligence (AI). Deaf and hard-of-hearing individuals face significant challenges when interacting with law enforcement, as communication barriers may hinder ef ective understanding and cooperation. Using advanced artificial intelligence techniques, specifically Convolutional Neural Networks (CNNs) and Long Short-Term Memory networks (LSTMs), the proposed system aims to enhance the ef iciency and ef ectiveness of law enforcement interactions with the deaf community. The integration of these neural network architectures allows for the recognition of a wide range of sign language expressions, ensuring adaptability to various signing styles and speeds. Real-time interpretation results are then provided, contributing to seamless communication and cooperation during police investigations.

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