Abstract

Communication between a specially abled person who is deaf and mute and a normal person is a challenging task. We are so used to communicating through speech but it is extremely important to remove the barriers of communication and facilitate smoother conversations. One of the ways of doing this is through Sign language. Thus, recognition of sign language through computerized systems and software development can be very helpful for real time communication. This paper reviews the different processes through which an assistive application can be made for facilitating communication with the people who are a part of the specially abled deaf and mute community. The main objective is to develop an image-based Sign Language recognizer software which can identify the hand gestures realtime, using Convolution Neural Networks.