A Deep Learning Driven Flask Level Enhanced Web Application for Efficient Communication System

Sign language is a crucial means of communication for millions worldwide but the effective learning of sign language is still hindered to this day. To overcome this, we propose a web application which makes use of neural networks and Mediapipe to create an E-Learning platform where users can learn, practice and assess their sign language skills. The main idea behind this initiative is that we can use the Mediapipe hands library to detect sign language gestures. Combining the power of neural networks with Mediapipe we can create an accurate way to detect sign language gestures. To further improve the efficiency and accuracy we also make use of a classifier. This classifier is used to create the Flask web application which serves as the sign language E-Learning platform. This platform comes equipped with resources for learning the sign language, interactive platform for practicing the sign language, and assessing your sign language skills. The combination of Mediapipe, Deep Learning and Flask together shows that new technologies can be used to reshape the E-learning industry and the platforms to be more inclusive and accessible.