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Sonification Mappings: Estimating Effectiveness, Polarities and Scaling in an Online Experiment

Sonification is a technique to present data arrays as sound, thereby taking advantage of the human ability to hear patterns that might otherwise not be apparent. Mappings from parameters of data to parameters of sound form the basis of parameter-mapping sonification. The choice of mappings and their design can influence both the utility of the sonification system and the ability of users to interpret the sounds. In this article the authors demonstrate the use of a time-efficient methodology with an experimental online platform for assessing mappings. Experiments explored the effectiveness of various mappings, and the discussions explore the implications of each approach. Based on the responses of 100 participants in an online Magnitude Estimation experiment, the effectiveness of 16 data-sound mappings was explored. Results showed that mappings involving certain sound parameters were generally effective, while those using other sound parameters varied in their effectiveness. In some cases the ability to interpret mappings and the polarities with which they were perceived varied among individuals using them. The mappings that used the tempo parameter were generally perceived effectively, while those using other sound parameters varied. Exploratory observations suggest that differences among participants might be related to different levels of musical experience.

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JAES Volume 66 Issue 12 pp. 1016-1032; December 2018
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Permalink: http://www.aes.org/e-lib/browse.cfm?elib=19875

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