AI-DRIVEN ADAPTIVE READING AND COGNITIVE SUPPORT SYSTEM FOR DYSLEXIA

Dyslexia is a neurodevelopmental learning difficulty that affects reading accuracy, fluency, and language processing in children despite normal intelligence.Traditional teaching methods and many existing digital tools lack personalized feedback, real-time evaluation, and offline accessibility, limiting their effectiveness for dyslexic learners.This paper presents an AI-driven adaptive reading and cognitive support system designed to assist children with dyslexia through guided reading and speech-based evaluation.The proposed system integrates offline speech-to-text for analyzing spoken reading, text-to-speech for correct pronunciation guidance, and rhythm-based word highlighting to support reading pace and focus.Reading performance is evaluated at the word level to identify errors, calculate accuracy, and provide constructive feedback.Performance data is stored locally to enable progress tracking while ensuring privacy and reliability.Experimental evaluation indicates improvements in reading accuracy, fluency, and learner engagement.The system provides a cost-effective, offline, and child-centric solution that supports dyslexic learners in home and educational environments.