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Replicating semantic connections made by visual readers for a scanning system for nonvisual readers

Published: 22 October 2012 Publication History

Abstract

When scanning through a text document for the answer to a question, visual readers are able to quickly locate text within the document related to the answer while simultaneously getting a general sense of the document's content. For nonvisual readers, however, this poses a challenge, especially when the relevant text is spread out or worded in a way that can't be searched for directly. Our goal is to make the scanning experience quicker for nonvisual readers by giving them an experience similar to that of visual readers. To do this we first determined what visual scanners focused on by using an eye-tracker while they scanned for answers to complex questions. Resulting data revealed that text with loose semantic connections to the question are important. This paper reports on our efforts to develop a method that automatically replicates the connections made by visual scanners. Ultimately, our goal is a system that replicates the visual scanning experience, allowing nonvisual readers to quickly glean information in a manner similar to how visual readers glean information when scanning. This work stems from work with students who are nonvisual readers and is aimed at making their school experience more equitable with students who scan visually.

References

[1]
Felbaum, C. 1998. WordNet an Electronic Database, Boston/Cambridge: MIT Press.
[2]
Salton, G. and Buckley, C. 1988. "Term-weighting approaches in automatic text retrieval." Information Processing & Management, 24 (5): 513--523.
[3]
Yarrington, D. and McCoy, K. 2010. "Automated Skimming in Response to Questions for NonVisual Readers." NAACL: SLPAT Workshop, Los Angeles, Ca.

Cited By

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  • (2016)Classification via Hidden Markov Trees for a Vision-Based Approach to Conveying Webpages to Users with Assistive Needs2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2016.0124(695-700)Online publication date: Oct-2016

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      cover image ACM Conferences
      ASSETS '12: Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility
      October 2012
      321 pages
      ISBN:9781450313216
      DOI:10.1145/2384916

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 22 October 2012

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      Author Tags

      1. assistive technology
      2. natural language processing
      3. text scanning
      4. word clustering

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      • (2016)Classification via Hidden Markov Trees for a Vision-Based Approach to Conveying Webpages to Users with Assistive Needs2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2016.0124(695-700)Online publication date: Oct-2016

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