Published Paper Details:

Differently abled people like deaf and dumb people use sign language for communicating with others. It is usually found difficult to communicate with them due to a lack of understanding of the universal sign language. This project aims to develop an application that will translate sign language into text, thereby reducing the communication gap between normal people and people with speech impairment. This application was developed using a deep learning algorithm which is CNN (Convolutional Neural Network). The model was trained on ASL (American Sign Language) based gestures. ASL is a universal language and contains 26 alphabets of well-distinguished images that can be used to train the model. The objective of this project is for the camera attached to the computer will capture the gestures of the hand and the feature extraction is used to recognize the hand gesture then based on the hand gesture the required text will be displayed on the screen. This application aims at bridging the gap in the process of communication between Deaf and Dumb people from the rest of the world.