Title:
Evaluating the magnitude estimation approach for designing sonification mapping topologies

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Ferguson, Jamie
Brewster, Stephen
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Abstract
A challenge in sonification design is mapping data parameters onto acoustic parameters in a way that aligns with a listener's mental model of how a given data parameter should sound. Studies have used the psychophysical scaling method of magnitude estimation to systematically evaluate how participants perceive mappings between data and sound parameters - giving data on perceived polarity and scale of the relationship between the data and sound parameters. As of yet, there has been little research investigating whether data-to-sound mappings that are designed based on results from these magnitude estimation experiments have any effect on usersメ performance in an applied auditory display task. This paper presents an experiment that compares data-to-sound mappings in which the mappingメs polarity is based on results from a previous magnitude estimation experiment against mappings whose polarities are inverted. The experiment is based around a simple task in which participants need to rank WiFi networks based on how secure they are, where security is represented using an auditory display. Results suggest that for a simple auditory display like the one used here, whether or not the polarities of the data-to-sound mappings are based on magnitude estimation does not have a substantial effect on any objective performance measures gathered during the experiment. Finally, potential areas for future work are discussed that may continue to investigate the problems addressed by this paper.
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2019-06
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Licensed under Creative Commons Attribution Non-Commercial 4.0 International License.