Lexi Read (Dyslexic Kid Helper)

Abstract

Conventional reading methods and inaccessible learning materials make it difficult for dyslexic children to improve their reading fluency and comprehension, while existing educational tools often lack personalized, interactive support. To address this challenge, this paper proposes Dyslexic Kid Helper, a user-centric web application designed to assist dyslexic children by providing an interactive, engaging, and supportive literacy experience. The system is developed utilizing Python Flask for a highly compatible web architecture , Tesseract Optical Character Recognition (OCR) to extract text from images and PDFs , and OpenAI GPT to power advanced comprehension features like instant definitions and paragraph simplification. Furthermore, the application is Docker-ready to ensure efficient deployment, scalability, and cloud hosting. By transforming complex text into accessible formats and delivering synchronous speech synthesis, the platform enables independent learning while offering a seamless, dyslexia-friendly user experience featuring tailored fonts and minimal distractions. In summary, Dyslexic Kid Helper acts as a comprehensive assistive learning solution, effectively combining AI and machine learning techniques to address the unique challenges faced by dyslexic children.

Introduction

The text highlights the difficulties faced by children with dyslexia in traditional reading environments, where standard text formats hinder their ability to develop reading fluency and comprehension. These challenges often require continuous support from teachers or parents, limiting independent learning.

Although existing assistive technologies like OCR and basic text-to-speech tools help convert text into more accessible formats, they lack advanced features such as personalized learning, comprehension support, and user-friendly interfaces tailored for dyslexic learners.

To address these gaps, the proposed system, Dyslexic Kid Helper, is an interactive web-based application designed to enhance reading skills through a more engaging and supportive approach. It uses OCR to extract text from images, PDFs, or documents, and integrates AI to simplify content, generate quizzes, and provide real-time speech with word highlighting. The system also tracks reading progress, offers personalized feedback, and includes secure user authentication.

Overall, the solution aims to promote independent learning, improve comprehension, and build confidence among dyslexic children by combining real-time assistance, adaptive features, and a dyslexia-friendly interface.

Conclusion

The proposed Dyslexic Kid Helper successfully demonstrates the application of modern web technologies to build an intelligent and scalable assistive reading support solution. The system enables users to extract text from learning materials, analyze historical reading trends, and receive real-time pronunciation feedback, thereby supporting interactive and confidence-building educational experiences. The implementation using Python Flask, Tesseract OCR, and OpenAI GPT ensured secure access, efficient text data handling, and smooth system performance. The Docker-ready modular architecture facilitated real-time synchronization between system components and allowed seamless integration of AI text simplification and natural speech synthesis functionalities. Future enhancements may include augmented reality (AR) reading support, multilingual voice assistance, detailed parent and teacher dashboards with analytics, and support for a wider range of digital learning formats. Cloud-based scaling and personalized reading recommendations can further improve usability and system reach. Overall, Dyslexic Kid Helper represents a practical and efficient solution for automated reading assistance, offering significant value to neurodivergent learners in today’s dynamic digital education environment.

References

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Copyright

Copyright © 2026 Ninad Muthe, Piyush Pradhan, Payal Bora, Yash Choutele, Prof. Anita Yadav. This 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.