DysWebxia is a model that integrates the findings from the PhD thesis of Luz Rello (June 2014) that includes studies with more than 150 people with dyslexia using eye tracking to make the texts more readable by modifying the content and presentation of the text.
This research was conducted with funding from Generalitat de Calaluyna (FI doctoral fellowship) at Web Research Group & Natural Language Processing Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra.
Abstract: Worldwide, 10% of the population has dyslexia, a cognitive disability that reduces readability and comprehension of written information. The goal of this thesis is to make text more accessible for people with dyslexia by combining human computer interaction validation methods and natural language processing techniques. In the initial phase of this study we examined how people with dyslexia identify errors in written text. Their written errors were analyzed and used to estimate the presence of text written by individuals with dyslexia in the Web. After concluding that dyslexic errors relate to presentation and content features of text, we carried out a set of experiments using eye tracking to determine the conditions that led to improved readability and comprehension. After finding the relevant parameters for text presentation and content modification, we implemented a lexical simplification system. Finally, the results of the investigation and the resources created, lead to a model, DysWebxia, that proposes a set of recommendations that have been successfully integrated in four applications.