Bayesian Explanation of the Effects of Tactile Feedback on the Affective Evaluation of Switch Sounds

摘要

In our previous study, the effects of tactile feedback on the affective evaluation of switch sounds were examined throughauditory and tactile evaluation experiments using 15 switches, and it was shown that these effects could be modeled using multipleregression analyses. However, the reason why the effects can be modeled by multiple regression analyses remains unanswered. In thisstudy, extended experiments were conducted using 25 switches. In the auditory evaluation experiment, using 26 adjective pairs on 7-point category scales, two groups consisting of 22 subjects each participated as operators and listeners, respectively. In the tactileevaluation experiment, using 16 adjective pairs, another group of 52 subjects participated. The results of both experiments wereanalyzed, separately, using factor analyses, with the three factors of potency, evaluation, and activity being extracted for bothexperiments. The factor scores of the operators were modeled using multiple regression analyses with the factor scores of listeners andtactile evaluations. Another modeling was conducted based on Bayes’ theorem, wherein the factor scores of listeners and operatorswere regarded as prior and posterior distributions, respectively, with the tactile factor scores being regarded as likelihood. The fact thatthese two models show almost the same estimation performance suggests that the effects of tactile feedback on the affective evaluationof switch sounds are modeled well by the multiple regression analysis because Bayesian multisensory integration is the origin of thecross-modal effects. This can be understood by the fact that the estimation equations of both models are essentially the same.