Virtual Reality and Augmented Reality in Sign Language Recognition: A Review of Current Approaches
Abstract
This paper delivers a comprehensive review of the current approaches to Sign Language Recognition (SLR) using Virtual Reality (VR) and Augmented Reality (AR) technologies. Sign language is essential for communication within the deaf and hard-of-hearing community, and traditional SLR methods have faced several challenges, including limited gesture recognition, lack of context awareness, and scalability. VR and AR, with their immersive and interactive environments, offer promising solutions to overcome these limitations. This review explores how VR and AR can enhance SLR by providing real-time feedback, personalized learning experiences, and more dynamic and engaging systems. It also examines the integration of VR and AR with advanced technologies such as machine learning and computer vision, which have significantly enhanced the accuracy and efficiency of sign language recognition. Despite progress, challenges related to hardware limitations, cultural diversity, and user experience remain. The paper concludes by highlighting future directions, including advancements in AI, increased affordability, and the need for interdisciplinary collaboration to ensure the development of inclusive, scalable, and accessible SLR systems
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