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DysWebxia: a model to improve accessibility of the textual web for dyslexic users

DysWebxia: a model to improve accessibility of the textual web for dyslexic users DysWebxia: A Model to Improve Accessibility of the Textual Web for Dyslexic Users Luz Rello NLP and Web Research Groups, Department of Information and Communication Technologies, Universitat Pompeu Fabra C/ TÃ nger 122-134, 08018 Barcelona luz.rello@acm.org Abstract The goal of this research is to make textual content in the Web --especially in Spanish and English-- more accessible to people with dyslexia. The techniques that we will use to make the Web more accessible are Natural Language Processing (NLP) for its content (text) and Web design guidelines for its layout. To find out which solutions tackle better our purpose we will test a diverse set of Web pages examples. The main methodology to evaluate these examples will be eye tracking using regular and dyslexic students. In the case that our findings show that there are strategies that make the Web more accessible for dyslexic users, we plan to develop and application which includes such results, transforming a regular Web site into a dyslexic friendly Web site. Introduction Broadly, this thesis addresses a real world problem: Web accessibility for dyslexic users. Given that dyslexia is a learning disability that affects language, we can assume that accessibility can be approached from http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGACCESS Accessibility and Computing Association for Computing Machinery

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