Paper Title
Deep Learning Technique for Detection of Sign Language

Language is a medium through which people can communicate and share their thoughts and words with each other and Sign language is one of the languages in which people make use of hand movements and gestures to express themselves. Normal people have trouble understanding and interpreting sign language's meaning. It really has become necessary to understand the sign language, so we need an interpreter, as expressed by the hearing impaired. The main facilitator in assisting hard-of-hearing people in interacting with the rest of society is learning sign language. The process by which a computer analyses and converts sign language gestures into understandable and human-readable text is known as "sign language detection." Those who have trouble hearing or speaking can communicate with ease by using Sign language detection software. Many different sorts of studies are being done to make this process easy and efficient. In this paper, we try to highlight the work and comparative study of that work done by researchers in American Sign Language using deep learning. Keywords - American Sign Language (ASL), Deep Learning (DL), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Principle Components Analysis (PCA), Histogram of Oriented Gradients (HOG)