AUTHOR=Benghanem Abdelghani , Valentin Olivier , Gauthier Philippe-Aubert , Berry Alain TITLE=Objective quantification of sound sensory attributes in side-by-side vehicles using multiple linear regression models JOURNAL=Frontiers in Acoustics VOLUME=2 YEAR=2024 URL=https://www.frontiersin.org/journals/acoustics/articles/10.3389/facou.2024.1477395 DOI=10.3389/facou.2024.1477395 ISSN=2813-8082 ABSTRACT=

The evaluation of sound quality is a pivotal area of research within audio and acoustics. The sound quality evaluation methods commonly used include both objective and subjective, the latter being time-consuming and costly as they rely on listening tests. This research work aims to investigate the use of predictive sound quality models as a way to objectively assess the Desire-to-buy of side-by-side vehicles, in a more efficient, faster, and less costly way than conventional methods. Multiple linear regression algorithms were used to validate the objective models derived from objective physical metrics and perceptual psycho-physical metrics. The sensory profile objective models reported in this paper were constructed using parsimonious linear Lasso and Elastic-net algorithms. Our results show that linear objective models effectively account for each of the perceptual attributes of the sensory profiles and the Desire-to-buy, while only requiring a few physical and psychophysical metrics.