Real-Time Sign Language Recognition using a Multimodal Deep Learning Approach
S. Amutha, Nakkella Shanmukh, Appala Naidu, Purini Vinod Kumar, G. Sri Satya Narayana · 2023
Sign language recognition is an important area of research that aims to provide greater access to communication and information for individuals who are deaf or hard of hearing. In this paper, we present a new approach for real-time sign language recognition using a multimodal deep learning approach. The proposed approach integrates video and inertial sensor data for improved recognition accuracy and robustness.The proposed approach uses a convolutional neural network (CNN) to extract features from the video data and a Recurrent neural network (RNN) is used to capture the temporal dynamics of the sign language gestures.Sign language recognition systems use technologies such as computer vision, machine learning, and artificial intelligence to analyze and understand the gestures and movements of the signer. These systems have the potential to improve the quality of life for individuals who are deaf or hard of hearing by providing them with greater access to communication and information in a variety of settings.