When headers are not there: design and user evaluation of an automatic topicalisation and labelling tool to aid the exploration of web documents by blind users

Abstract

Using headers to grasp a document's structure has been one of the main strategies employed by blind users on web documents when using screen readers. However, when headers are not available or not appropriately marked up, they can cause serious difficulties. This paper presents the design and evaluation of a tool for automatically generating headers for screen readers with topicalisation and labelling algorithms. The proposed tool uses Natural Language Processing techniques to divide a web document into topic segments and label each segment based on its content. We conducted an initial user study with eight blind and partially-sighted screen reader users. The evaluation involved tasks with questions answered by participants with information from texts with and without automatically generated headers. Results provided preliminary indicators of improvement in performance and reduction of cognitive load. The findings contribute to knowledge to improve tools to aid in text exploration. It also provides initial empirical evidence to be further explored to analyze the impact of automatically-generated headings in improving performance and reducing cognitive load for blind users.