Translation Assistant for Converting Sign Language to Text and Audio

Abstract

Sign Language Recognition (SLR) converts sign language motions into legible text or voice with the goal of assisting the hard of hearing in communicating. An outline of the most recent approaches, developments, and difficulties in SLR is provided in this abstract. It talks about how important SLR is to help the deaf and hard of hearing community be more inclusive and accessible so they can communicate with the general public more successfully. Convolutional neural networks (CNNs)this new developments in deep learning-based techniques that have demonstrated promising outcomes in SLR tasks, are also highlighted in the abstract. To improve the accuracy and practicality of SLR systems in real-world situations, it also tackles the requirement for strong datasets, effective feature extraction strategies, and model optimisation approaches.