Sign Language Recognition System using Machine Learning

Speech impediment is regarded as a legitimate handicap.Individuals with this handicap interact with others in a variety of ways.Sign language is one such popular way that they employ.Deaf individuals will be able to communicate with everyone, even those who do not understand sign language, thanks to the development of sign language applications.Through the use of sign language, our project seeks to close the communication gap between normal people and deaf dumb persons.The primary goal of this effort is to develop a vision-based system that can recognize sign language motions from video sequences.The rationale for using a vision-based system is that it offers a more straightforward and natural means of communication between humans and deaf dumb people.For those who are Deaf or Hard of Hearing, sign language is an essential communication tool.However, recognition and interpretation of signals automatically present substantial obstacles since sign languages are inherently visual.New directions for the development of sign language recognition systems have been made possible by developments in machine learning (ML) techniques in recent years.In this research, a unique machine learning-based sign language recognition system is proposed to bridge the communication gap between the Deaf community and the broader public.