ASL Real-Time Translator

This chapter delves into the development of an ASL Real-Time Translator, a groundbreaking tool designed to enhance communication between hearing and deaf individuals. The project employs deep learning and computer vision techniques to translate American Sign Language (ASL) gestures into text in real-time. The architecture comprises a Web interface, server, word constructor, predictor, and user, with real-time communication facilitated by WebRTC. The predictor, a CNN model converted to JavaScript using TensorFlow.js, accurately translates ASL gestures into meaningful sentences. The implementation faced challenges such as RAM and GPU limitations, but the final model achieved over 95% accuracy on testing datasets. The project's future scope includes extending the translator to other sign languages and deploying it on a global server for widespread access.