Preprint
Article

This version is not peer-reviewed.

Machine Learning Based Dyslexia Screening Using Multimodal Tests

Submitted:

12 October 2026

Posted:

14 October 2026

You are already at the latest version

Abstract
Dyslexia is a common problem that affects how people read and write. It is not because they are not smart. Because their brain works a little differently. It is really important to find out if someone has dyslexia so we can help them with their reading and writing. The problem is that the ways we have now to figure out if someone has dyslexia are not very good. They take a lot of time. Are not always right. In this paper we are talking about a way to find out if someone has dyslexia. This way uses computers to look at how people write and talk. We use something called Natural Language Processing to look at the words and sentences that people write. We also use something called Sequence-to-Sequence to look at the patterns in their writing. This helps us to see if someone has dyslexia or not. We tried out our way with some tests and it worked pretty well. It was able to tell if someone had dyslexia or not 63 percent of the time. This is really good because it means that we can use this way to help kids who have dyslexia. It is also a way because it is not too expensive. This means that teachers and parents can use it to help kids with dyslexia. Dyslexia is a problem that we can help with if we can just find out who has it. Our new way is a step, in the right direction. Dyslexia detection is important. Our system can help with dyslexia detection.
Keywords: 
;  ;  ;  ;  
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.