Abstract

For those who are deaf or hard of hearing, sign language is essential as their main form of communication. using ease, sign language gestures may be translated into written or spoken words in real time using the Sign Language Translator, and vice versa. This system interprets and communicates sign language gestures by utilising computer vision and natural language processing (NLP). Given that sign language uses a wide range of hand movements to communicate meaning, it might be difficult to identify certain motions by looking for patterns. Individuals communicate and engage using a variety of gestures. In this study, a humancomputer interface that can recognise motions in sign language and properly translate them into text is shown. The suggested method improves interpersonal communication by using convolutional neural networks and long short-term memory networks for gesture interpretation and detection