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@article{177787,
        author = {Esha Garg and Ishita Garg and Amrita Soney and M.P.S Bhatia},
        title = {Enhancing Accessibility: Leveraging Large Language Models for Indian Sign Language Translation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2683-2692},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177787},
        abstract = {This paper explores the use of machine learning algorithms and Large Language Models (LLMs) to enhance the translation of Indian Sign Language (ISL) into spoken languages. A hybrid model is proposed for gesture identification from video inputs, and an LLM is used to translate identified signs into text, ensuring grammatical correctness. The method addresses the lack of annotated ISL datasets and promotes inclusive AI applications that bridge barriers between sign language communities and technology. The results indicate the viability of developing AI systems that respect linguistic diversity while putting underrepresented languages on the map.},
        keywords = {large language model, indian sign language, deaf, hard of hearing, linguistic diversity},
        month = {May},
        }