SIGN LANGUAGE DETECTION USING MACHINE LEARNING

SIGN LANGUAGE DETECTION USING MACHINE LEARNING

Rushikesh Bhalerao, Piyush Bhujbal, Shreyas Waghchaure, Rutik Malave, Krushna Chavan

Sir Visvesvaraya Institute of Technology

A/p :Chincholi, Tal.:Sinnar,Dist.:Nashik,Maharashtra,India-422102.

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Abstract- The dumb and deaf people have the most common problem of communication with the normal people.The physically challenged people who are disabled to talk and hear need to find a way of communication medium through which they can express their thoughts and solve their problems. Thus, to work upon it some experts designed a Sign Language. This language is different for different countries and then implemented it upon performing experiments over long times. The Indian Sign Language is probably the topic of study and interest. The thing is because of its simplicity and accuracy anyone can understand what the handicapped is trying to say.

In the above review we a team of four students under the guidance of our project guide are just giving a rough improvement and adding some automation techniques with Machine Learning and Computer Vision through which we are attempting to create the Indian Sign Language Detection algorithm through Deep Neural Networks. The main aim of this project is to create a simple, easy and ready to use application that predicts the symbol shown by the user in front of the camera and then the ML model in the backend predicts the output and shows it live on the screen.

Keywords: , Skin Segmentation, SVM, CNN,KNN,.