Supervised and Unsupervised Data Engineering for Multimedia Data

1SLRRT: Sign Language Recognition in Real Time

Monika Lamba^1* and Geetika Munjal²

¹Department of Computer Science and Engineering (CSE), The NorthCap University, Gurugram, India

²Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, India

Abstract

An application called Sign Language Recognition (SLR) can recognise a variety of non-identical letter movements and translate them into text. In the area of science and technology, this application is extremely significant. It can be used in a variety of machine learning-based applications, including virtual reality. The purpose of the chapter is to develop a convolutional neural network that will recognise the signs captured or focused from the video capture and in turn provide us with correct or accurate output based on text and to improve the accuracy of the real-time sign language recognition via scanning and detecting that would aid other physically challenged individuals. For all individuals who want assistance in communicating with the rest of society, it offers an offline application. In order to produce quick, precise results and to ensure that the material isn’t lost during the evaluation process, it tries to evaluate gestures more efficiently. Real-time sign language recognition involves first identifying images from a video feed that has been acquired using a machine learning model, then identifying edges and vertices, and then determining the desired result using a convolutional neural network. ...