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@article{180558,
        author = {Dr.Y.Baby Kalpana and Vijayalakshmi S and T.Manojpraphakar},
        title = {AERON – AN ANSWER ENGINE FOR  ILLITERATE PEOPLE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2532-2538},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180558},
        abstract = {Digital literacy remains a significant barrier for underserved populations, especially children and individuals with limited language proficiency. This paper introduces Aeron, a web-based intelligent question-answering system tailored to bridge this gap using simplified AI-generated responses. Built upon a fine-tuned generative language model using OpenAI and Gemini APIs, the system delivers real-time, easy-to-understand answers across diverse domains such as education, health, and technology. Unlike conventional AI tools, Aeron is trained on a custom-curated dataset with simplified language structures, optimized for accessibility. The model is hosted on Google Colab and interacts via a Node.js backend and a React-based frontend. Experimental evaluation demonstrates the system's effectiveness in generating clear, jargon-free responses, with an average Flesch-Kincaid readability score improvement of 37% over baseline outputs. Aeron exemplifies an inclusive AI system that enables digital empowerment through linguistic simplicity, intuitive UI, and extensibility for low-resource environments.},
        keywords = {Accessible AI, Language Simplification, NLP for Low Literacy, Generative Models, React-NodeJS Web Application, Education Technology.},
        month = {June},
        }