Understanding Pattern Recognition Through Sound with Considerations for Developing Accessible Technologies

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Abstract

This work explores whether audio feedback style and user ability influences user techniques, performance, and preference in the interpretation of node graph data among sighted individuals and those who are blind or visually impaired. This study utilized a posttest-only basic randomized design comparing two treatments, in which participants listened to short audio clips describing a sequence of transitions occurring in a node graph. The results found that participants tend to use certain techniques and have corresponding preferences based on their ability. A correlation was also found between equivalently high feedback design performance and lack of overall feedback design preference. These results imply that universal technologies should consider avoiding utilizing design constraints that allow for only one optimal usage technique, especially if that technique is dependent on a user’s ability.

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Darmawaskita, N., & McDaniel, T. (2020). Understanding Pattern Recognition Through Sound with Considerations for Developing Accessible Technologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12426 LNCS, pp. 208–219). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60149-2_17

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