Predictive web automation assistant for people with vision impairments

  • Authors:
  • Yury Puzis;Yevgen Borodin;Rami Puzis;I.V. Ramakrishnan

  • Affiliations:
  • Charmtech Labs LLC, Stony Brook, NY, USA;Charmtech Labs LLC, Stony Brook, NY, USA;Ben-Gurion University, Beer-Sheva, Israel, Israel;Charmtech Labs LLC, Stony Brook, NY, USA

  • Venue:
  • Proceedings of the 22nd international conference on World Wide Web
  • Year:
  • 2013

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Abstract

The Web is far less usable and accessible for people with vision impairments than it is for sighted people. Web automation, a process of automating browsing actions on behalf of the user, has the potential to bridge the divide between the ways sighted and people with vision impairment access the Web; specifically, it can enable the latter to breeze through web browsing tasks that beforehand were slow, hard, or even impossible to accomplish. Typical web automation requires that the user record a macro, a sequence of browsing steps, so that these steps can be automated in the future by replaying the macro. However, for people with vision impairment, automation with macros is not usable. In this paper, we propose a novel model-based approach that facilitates web automation without having to either record or replay macros. Using the past browsing history and the current web page as the browsing context, the proposed model can predict the most probable browsing actions that the user can do. The model construction is "unsupervised". More importantly, the model is continuously and incrementally updated as history evolves, thereby, ensuring the predictions are not "outdated". We also describe a novel interface that lets the user focus on the objects associated with the most probable predicted browsing steps (e.g., clicking links and filling out forms), and facilitates automatic execution of the selected steps. A study with 19 blind participants showed that the proposed approach dramatically reduced the interaction time needed to accomplish typical browsing tasks, and the user interface was perceived to be much more usable than the standard screen-reading interfaces.