Communication through Hands in Sign Language - A CNN Collaborative Study

Abstract

A system of communication called sign language makes use of visual motions and signals. The only form of communication for the deaf and dumb community and others with hearing impairments is sign language. Understanding sign language is so much difficult for a normal person. As a result, connecting with the wider public has always been extremely difficult for the minority community. In this study, we suggested a novel deep learning-based method for identifying sign language that can help normal and deaf individuals communicate more easily. In order to identify real-time sign language, we first created a dataset with 11 sign terms. Our bespoke CNN model was trained using these sign words. Prior to the CNN model being trained, we preprocessed the dataset. Our results show that the customized CNN model can attain the greatest accuracy of 98.6%.