The causal properties of sounds predict their recognition and misidentification Free

One way to study human sound recognition is to investigate the reasons why sounds are sometimes misheard as coming from the wrong source. Understanding this cognitive process can not only help prevent undesirable sound confusions (e.g., auditory display design) but can also promote useful confusions (e.g., Foley effects, cognitive reappraisal for misophonia). We tested the hypothesis that sounds are more confusable if their source events share causal properties. In Expi.1, listeners assessed causal properties of everyday sounds (ESC-50 Dataset) by judging their actions (e.g., tapping), materials (e.g., metal), and causal agents (e.g., machines). Causal similarity between sounds was measured by the distance between their causal properties. In Exp. 2, new listeners identified these sounds with 90% accuracy. Using the distances obtained in Exp. 1, misidentifications were predicted with 91% sensitivity and 89% specificity. The causal properties that had the largest effect on recognition accuracy were predominantly actions (according to a Ridge regression). Additional experiments with our own recorded and synthesized sounds show that spectral degradation and temporal manipulation can cause significant changes in causal properties and source assignment. Altogether, these findings show that causal properties provide unique explanatory power for sound recognition and misidentification. [Work supported by REAM.]