Abstract:

The web holds incredible potential for blind computer users. Most web content is relatively open, represented in digital formats that can be automatically converted to voice or refreshable Braille. Software programs called screen readers can convert some content to an accessible form, but struggle on content not created with accessibility in mind. Even con- tent that is possible to access may not have been designed for non-visual access, requiring blind web users to inefficiently search for what they want in the lengthy serialized views of content exposed by their screen readers. Screen readers are expensive, costing nearly $1000, and are not installed on most computers. These problems collectively limit the accessibility, usability, and availability of web access for blind people.

Existing approaches to addressing these problems have not included blind people as part of the solution, instead relying on either (i) the owners of content and infrastructure to improve access or (ii) automated approaches that are limited in scope and can produce confusing errors. Developers can improve access to their content and administrators to their computing infrastructure, but relying on them represents a bottleneck that cannot be easily overcome when they fail. Automated tools can improve access but cannot address all concerns and can cause confusion when they make errors. Despite having the incentive to improve access, blind web users have largely been left out.

This dissertation explores novel intelligent interfaces enabling blind people to independently improve web content. These tools are made possible by novel predictive models of web actions and careful consideration of the design constraints for creating software that can run anywhere. Solutions created by users of these tools can be shared so that blind users can collaboratively help one another make sense of the web. Disabled people should not only be seen as access consumers but also as effective partners in achieving better access for everyone.

The thesis of this dissertation is the following: With intelligent interfaces supporting them, blind end users can collaboratively and effectively improve the accessibility, usability, and availability of their own web access.

Full Thesis:
Download Jeffrey P. Bigham’s Full Thesis

Thesis Advisor:
Richard E. Ladner

Award Date:
October 1, 2009

Institution:
University of Washington, Department of Computer Science and Engineering
Seattle, Washington, USA

Author Contact:
jbigham-ta-nullcs-tod-rochester-tod-edu