Speed Reading Tool Powered by Artificial Intelligence for Students with ADHD, Dyslexia, and Short Attention Span

Abstract:This paper presents an artificial intelligence tool designed to assist students with dyslexia, ADHD, and short attention spans in processing text-based information more efficiently. The proposed solution addresses both cognitive and visual reading barriers by pairing a cloud-hosted large language model with adaptive typographic formatting. At its core, the tool streams a request to Google's Gemini API to generate accurate, context-aware summaries in real time, removing the need to host or fine-tune a local model. The application accepts pasted text as well as uploaded .txt, .pdf, and .docx files, extracting and summarizing each source independently. To further optimize readability, the system layers a custom half-word bolding technique with a second pass that identifies and highlights genuine keywords using part-of-speech tagging and frequency ranking, and lets users manually adjust line, word, letter, and text spacing. Deployed through a lightweight Flask web framework that proxies requests to Gemini, the system provides a highly personalized and accessible user interface. Initial results demonstrate that this integrated approach significantly improves both reading speed and comprehension, enabling targeted students to digest complex textual data with greater focus.

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

arXiv:2307.14544 [cs.CL]

(or arXiv:2307.14544v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2307.14544 Focus to learn more arXiv-issued DOI via DataCite

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