Speed Reading Tool Powered by Artificial Intelligence for Students with ADHD, Dyslexia, and Short Attention Span
This paper presents an AI-powered web tool that enhances reading efficiency and comprehension for students with ADHD, dyslexia, and short attention spans by combining real-time, context-aware text summarization via Google's Gemini API with adaptive typographic formatting and customizable visual adjustments.
Original paper dedicated to the public domain under CC0 1.0 (http://creativecommons.org/publicdomain/zero/1.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine the internet as a massive, endless library where books are being written faster than anyone can read them. For most people, this is just a lot of information, but for students with ADHD, dyslexia, or short attention spans, this library can feel like a maze with no exit. The challenge isn't just that there is too much to read; it's that the brain struggles to filter the noise, keep focus, and decode the words without getting tired or overwhelmed. This is where a specific corner of science called Artificial Intelligence (AI) steps in. Think of AI not as a robot taking over, but as a super-smart, tireless librarian who can read a thousand books in a second and then whisper the most important parts to you. The key idea here is "Large Language Models," which are like giant digital brains trained on almost all the text ever written. They don't just memorize words; they understand how sentences fit together, allowing them to summarize complex stories into bite-sized pieces. By combining this digital brain with clever ways of displaying text on a screen, researchers are trying to build a bridge that helps struggling readers cross the gap between "too much text" and "I understand."
This paper introduces a new tool designed to be that bridge, acting like a personal reading assistant powered by Google's "Gemini" AI. Instead of asking a student to slog through a 20-page assignment, the tool acts as a high-speed translator, turning dense documents into clear, concise summaries in real-time. The system is built to handle the messy reality of student life: you can paste a block of text, or upload a .txt, .pdf, or .docx file, and the tool treats each one as its own story. It doesn't just spit out a summary, though; it streams the text to you as it's being written, so you don't have to wait for the whole thing to finish before you can start reading.
What makes this tool special is how it dresses up the text to make it easier for the brain to catch. Imagine reading a sentence where every other word is bolded, like a rhythmic drumbeat guiding your eyes forward; that's the "half-word bolding" technique the authors use to keep your focus moving. But they didn't stop there. Once the summary is done, the tool does a second pass, acting like a highlighter pen that knows exactly what matters. It uses a method called "part-of-speech tagging" to identify the "stars" of the sentence—like names, numbers, and important adjectives—and highlights them separately from the rest of the text. It even creates a little list of "keyword chips" at the bottom, so you can scan the main ideas at a glance without reading every single word.
The paper suggests that this combination of AI summarization and visual tricks works well for students with ADHD and dyslexia. In their initial tests, the tool seemed to help these students process information faster and with better focus. The authors note that by using a cloud-based AI (Gemini) rather than trying to run a heavy computer program on a student's own laptop, the tool stays light and fast. It also offers a "control panel" where users can manually adjust the spacing between lines, words, and letters, letting them customize the page to fit their own visual needs. While the results are promising, the paper is careful to say that the quality of the summary depends on the AI's performance and that the tool works best when the text isn't too complex. The researchers see this as a starting point, with future plans to handle even trickier files, like scanned images, and to make the keyword highlighting even smarter. For now, it stands as a playful, practical experiment in using technology to make reading less of a battle and more of a breeze.
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