Abstract

Abstract The car interior is becoming quieter and other sounds are now exposed to user perception, such as the sound produced by interface buttons when actuated. So, the functional role of the button sound on interface operation and its aesthetic and emotional role on the user experience are now more important than before. However, little research and design effort has been paid to understand how to design buttons that produce a pleasant sound. Moreover, the button’s sound requirements received by interface manufacturers are ill-defined, insufficient or even inexistent, and consequently their conversion into specifications for manufacturing is problematic and leads to long and costly development processes. The purpose of this paper is to contribute to identify relevant acoustic parameters that explain the users sound preferences. Data on preference subjective judgments were collected and buttons acoustic signals were measured allowing the development of preference models based on partial least squares regression and neural networks methods. The former was successful in selecting the relevant parameters to describe the preference ratings of the buttons sound. The later, dealing with the non-linear nature of acoustic perception, was able to predict preferences based on the relevant parameters.

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