Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{171722,
        author = {SHIJINA B and Dr.B.Ben Sujitha},
        title = {Breaking Barriers: A Survey of Sign Language Translation Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {833-837},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171722},
        abstract = {Real-time sign language translator systems represent a significant breakthrough in technology aimed at fostering seamless communication between the deaf community and the hearing world. Here we explores the relevance and impact of real-time sign language translator systems in bridging the communication gap for individuals who use sign language as their primary mode of communication. By leveraging cutting-edge technologies such as computer vision, machine learning, and natural language processing, these systems have the capability to interpret and translate sign language gestures into spoken language or text in real time. This capability revolutionizes communication accessibility in diverse settings including educational institutions, workplaces, healthcare facilities, legal proceedings, and public events. Our survey aimed to analyse the advancements in real-time sign language translators developed over the past years .We analysed the current literature, technical reports, and conference papers on real-time sign language translation systems.},
        keywords = {real-time sign language translator, machine learning, Sign language Recognition, Tensor Flow Object Detection, gestures.},
        month = {January},
        }