Voice Based Sign Language Detection For Dumb People Communication Using Machine Learning

Abstract

Around 2.78% of the population in our nation cannot speak (dump). The fundamental way that two people engage is through communication. Since ancient times, people have used speech to interact with one another. Although science and technology have added comfort to human life, there are still some who are less fortunate who are battling to discover a solution that would make communication for them simpler. People who have trouble speaking utilise sign language that is based on hand movements. This programme enables the blind and deaf to interact with seeing people despite their communication challenges. This study suggested a novel method of FFNN (Feed Forward Neural Network) prototype that can automatically recognise sign language to assist normal individuals in more effective communication with those who are hearing, speech, or visually challenged. This system identified of the hand signal feature point extraction given with Feed Forward point extraction given with Feed Forward neural network. Hand Gesture Recognition with Voice Process system using HMM (Hidden Markov model) is used to provide the communication for dump people and the normal people.