ACCESSING INFORMATION FOR PHYSICALLY IMPAIRED PERSONS USING SIGN LANGUAGE DETECTION SYSTEM

ACCESSING  INFORMATION FOR PHYSICALLY IMPAIRED PERSONS USING SIGN LANGUAGE DETECTION SYSTEM

V.K.Karthikeyan M.E.,[Ph.D], A.Premkumar, S.K.Samvardhan,E.Sashibalan, S.Vishnu Balan

V.K.Karthikeyan M.E.,[Ph.D]Department of Computer Science and EngineeringHindusthan College of Engineering and Technology

E-mail: karthikeyan.cse@hicet.ac.in

A.Premkumar Department of Computer Science and Engineering Hindusthan College of Engineering and Technology

E-mail: 20104137@hicet.ac.in

S.K.Samvardhan Department of Computer Science and Engineering Hindusthan College of Engineering and Technology

E-mail:20104152@hicet.ac.in

E.Sashibalan Department of Computer Science and Engineering Hindusthan College of Engineering and Technology

E-mail: 20104157@hicet.ac.in

S.Vishnu Balan Department of Computer Science and Engineering Hindusthan College of Engineering and Technology

E-mail: 20104188@hicet.ac.in

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ABSTRACT - This paper presents a novel approach to improving information accessibility for physically impaired individuals, specifically those with hearing impairments, through the development and implementation of a sign language detection system. The system leverages state-of-the-art machine learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), combined with advanced computer vision techniques to accurately recognize and interpret sign language gestures in real-time. This technology is designed to bridge the communication gap by converting recognized gestures into text or spoken language, thereby facilitating access to a wide range of digital information and communication platforms.