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Description
Although many data visualization diagrams can be made accessible for individuals who are blind or visually impaired, they often do not present the information in a way that intuitively allows readers to easily discern patterns in the data. In particular,

Although many data visualization diagrams can be made accessible for individuals who are blind or visually impaired, they often do not present the information in a way that intuitively allows readers to easily discern patterns in the data. In particular, accessible node graphs tend to use speech to describe the transitions between nodes. While the speech is easy to understand, readers can be overwhelmed by too much speech and may not be able to discern any structural patterns which occur in the graphs. Considering these limitations, this research seeks to find ways to better present transitions in node graphs.

This study aims to gain knowledge on how sequence patterns in node graphs can be perceived through speech and nonspeech audio. Users listened to short audio clips describing a sequence of transitions occurring in a node graph. User study results were evaluated based on accuracy and user feedback. Five common techniques were identified through the study, and the results will be used to help design a node graph tool to improve accessibility of node graph creation and exploration for individuals that are blind or visually impaired.
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Barrett Honors College theses and creative projects are restricted to ASU community members.

Details

Title
  • Developing a Node Graph Tool: Pattern Recognition Through Sound
Contributors
Date Created
2019-12
Resource Type
  • Text
  • Machine-readable links