Sonification mappings: Estimating effectiveness, polarities and scaling in an online experiment - Axon, L; Goldsmith, M; Creese, S (Audio Engineering Society, 2018)
Mappings from parameters of data to parameters of sound form the basis of parameter-mapping sonification. The mappings used and their design can impact the utility of sonification systems, and the ability of users to interpret them. While some prior work has explored approaches to discovering effective mapping designs, there is a need to add to knowledge on the perception of mappings, and to produce efficient methodologies using which sonification designers can explore new mappings. In this article, we demonstrate the use of a time-efficient methodology using an online experiment platform for assessing data-sound mappings. We explore approaches to measuring the effectiveness of data-sound mappings, and reflect on the implications of each approach for the use of mappings in sonification design. Based on the responses of 100 participants in an online Magnitude Estimation experiment, we assess the effectiveness of 16 data-sound mappings, and indicate suitable polarities and scaling exponents for their design. Our results show that mappings involving certain sound parameters were generally effective, while those using other sound parameters varied in their effectiveness across mappings to different data parameters. In some cases, the ability to interpret mappings, and the polarities with which they were perceived, varied between individuals