Instantaneous Sign Language Interpretation Leveraging Advanced Neural Networks

: Native sign language is most commonly used by hearing disabled individuals for communication Deep learning algorithms are making way for motion and gesture detection and classification. This topic is getting more popular due to advancement in deep learning techniques and computer vision. CNN’s assistance toward closing the gap between signers and non-signers. A web app is created with the trained model to make it publicly available. When input this image, it has used computer vision and neural network and detects the signs and gives the respective text as output. The recognized gestures are then converted into text or voice output, which can be used to display on the screen, or using some speaker to speak. The system captures video frames of sign language gestures using a camera. In this paper, we are developing a sign language recognition system using deep learning techniques in real time. The system is an intended solution to a problem by providing real-time translation of sign language gestures to either text or speech, serving to bridge the gap between deaf and hearing individuals.