Simulation and Analysis of Hand Gesture Recognition for Indian Sign Language using CNN

Abstract

Sign Language Recognition is a device or program to help deaf and mute people. However, communication has always been difficult for a person with verbal and physical disabilities. Sign language recognition communication between the average person and the disabled using this device easily communicates with people who cannot communicate with the average person, this program reduces the communication gap between people. In total, the world has a population of about 15 -20% of the deaf and mute population which is a clear indication of the need for a Sign Language Awareness Program. Different methods are used to identify sign language but they are not effective due to the economic and commercial situation so we use this cheap and affordable method for people. Therefore, sign language recognition systems based on image processing and sensory networks are preferred over gadget programs as they are more accurate and easier to implement. This paper aims to create an easy-to-use and accurate sign language recognition system trained in the neural network thus producing text and speech input.