Dyslexia Detection: Using Decision Tree Algorithm

Dyslexia Detection: Using Decision Tree Algorithm

Rishi Jain, Pranav Patel, Tanaya Jadhav, Kimaya Joshi, Ishita Jasuja

Department of Information Technology (IT) Vishwakarma Institute of Technology, Pune, 411037, Maharashtra, India

Abstract - This study unveils a novel machine learning paradigm for dyslexia detection that amalgamates handwriting analysis, pronunciation assessment, and dictation evaluation into a cohesive diagnostic framework. By integrating these distinct linguistic facets into a unified dataset, we have formulated a predictive algorithm with remarkable precision in identifying dyslexia-linked patterns. Such innovation offers a rapid and non-intrusive diagnostic instrument poised to transform the landscape of dyslexia screening within educational frameworks. Our method, by minimizing the need for intensive resource allocation and complex testing procedures, presents a significant leap towards accessible and equitable educational support systems.

Keywords— Child Disorder, Dyslexia, Decision Tree, Levenshtein , OCR, Phonetic.