Left-handed voices? Examining the perceptual learning of novel person characteristics from the voice

We regularly form impressions of who a person is from their voice, such that we can readily categorise people as being female or male, child or adult, trustworthy or not, and can furthermore recognise who specifically is speaking. How we establish mental representations for such categories of person characteristics has, however, only been explored in detail for voice identity learning. In a series of experiments, we therefore set out to examine whether and how listeners can learn to recognise a novel person characteristic. We specifically asked how diagnostic acoustic properties underpinning category distinctions inform perceptual judgements. We manipulated recordings of voices to create acoustic signatures for a person's handedness (left-handed vs. right-handed) in their voice. After training, we found that listeners were able to successfully learn to recognise handedness from voices with above-chance accuracy, although no significant differences in accuracy between the different types of manipulation emerged. Listeners were, furthermore, sensitive to the specific distributions of acoustic properties that underpinned the category distinctions. We, however, also find evidence for perceptual biases that may reflect long-term prior exposure to how voices vary in naturalistic settings. These biases shape how listeners use acoustic information in the voices when forming representations for distinguishing handedness from voices. This study is thus a first step to examine how representations for novel person characteristics are established, outside of voice identity perception. We discuss our findings in light of theoretical accounts of voice perception and speculate about potential mechanisms that may underpin our results.