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Proceedings Paper

Use of natural sounds and metaphors for data perceptualization
Author(s): Suresh Kumar Lodha; Ellen Venable; David Marsh; Doanna Meads; Nguyet Manh; Casey Robinson; Krishna Roskin
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Paper Abstract

We describe three systems that use natural or event-based sounds as means of data delivery. In these systems we have mapped data to natural sounds using metaphors. In the first system we evaluate the use of sounds of air, horn, and train to convey ordered numeric values between 1 to 6. An example of the metaphor used here is the association of speed values to the sound of a moving train at different speeds. In the second system, we use sounds of ocean waves to convey whether the exposure in a protein structural alignment is buried, partially exposed or fully exposed. The metaphor used here is the association of sound with how exposed the user is with respect to the ocean. In the third system, we map animal sounds such as the sound of a roaring lion or a chirping bird to certain stocks based on user preferences. The behavior of the stocks are then sounded by the use of whistles and car crash to signify the movement in process of the stocks. An up whistling sound can be clearly associated with an uptrend. We present and discuss the results of user evaluation studies for all the three systems.

Paper Details

Date Published: 3 May 2001
PDF: 11 pages
Proc. SPIE 4302, Visual Data Exploration and Analysis VIII, (3 May 2001); doi: 10.1117/12.424927
Show Author Affiliations
Suresh Kumar Lodha, Univ. of California/Santa Cruz (United States)
Ellen Venable, Univ. of California/Santa Cruz (United States)
David Marsh, Univ. of California/Santa Cruz (United States)
Doanna Meads, Univ. of California/Santa Cruz (United States)
Nguyet Manh, Univ. of California/Santa Cruz (United States)
Casey Robinson, Univ. of California/Santa Cruz (United States)
Krishna Roskin, Univ. of California/Santa Cruz (United States)


Published in SPIE Proceedings Vol. 4302:
Visual Data Exploration and Analysis VIII
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Craig M. Wittenbrink; Matti Grohn, Editor(s)

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