Readability Enhancement for PDF Documents - Yu, Chen-Hsiang; Shelton, Zachary; Abou Nassif Mourad, Omar; Oulal, Mohamed A. (Frontiers in Computer Science, 2021)
Readability has been studied for decades, ranging from traditional paper reading to digital document reading, Web page reading, etc. Different audiences have different needs and the needs trigger the researchers to investigate innovative solutions. For example, in recent years, researchers have studied readability enhancement of English articles for non-native English readers, either on paper reading or hypertext document reading. Using a variety of methods, researchers were able to enhance the reading comprehension and the users’ satisfaction on hypertext document reading, such as changing content presentation with visual-syntactic text formatting (VSTF) format or Jenga format. In terms of dynamically changing content presentation for reading, one less explored format is Portable Document Format (PDF), which was traditionally viewed within a modern Web browser or Adobe Acrobat reader on the desktop. PDF format was standardized as an open format in 2008 and has been widely used to keep a fixed-layout content. However, a fixed layout document presents a challenge to apply existing transformation methods, not mention on mobile devices. In this paper, we not only present a system that uses a novel algorithm to decode PDF documents and apply content transformation to enhance its readability, but we also generalize it to a framework that allows the users to apply customizations and the developers to customize their needs. Although we used Jenga format as an example to enhance the readability of PDF documents, we envision the proposed framework can be used to adopt different customizations and transformation methods. The current result is promising, and we believe it is worth further investigation to make PDF documents readable and accessible for different populations, such as non-native English readers, people with dyslexia or special needs, etc.