Machine Learning-Based Audio Interface Model for Sign Language Recognition

Abstract

Due to the fact that most offices and educational institutions now operate from home, the work-from-home and study-from-home cultures have made it difficult to interact with persons who are deaf or hard of hearing. These people communicate within their society using sign language, which is not widely understood by others. Most of the time, as a result of this, they miss out on the opportunity to express their point in front of every one since they are ignored/passed over without receiving the necessary attention. In real-time, having an independent translator that can process photos and interpret signs quickly at the speed of streaming images is critical. We'll utilize TensorFlow Object Detection and Python to bridge the gap by creating an end-to-end bespoke object detection model that not only translates sign language in real time but also speaks it to others.