Human speech perception is highly adaptive: exposure to an unfamiliar accent quickly reduces the difficulty listeners might initially experience. How such rapid adaptation unfolds incrementally remains largely unknown. This includes questions about how listeners' prior expectations based on lifelong experiences are integrated with the unfamiliar speech input, as well as questions about the speed and success of adaptation. We begin to address these knowledge gaps through a combination of an incremental exposure-test paradigm and model-guided data interpretation. We expose US English listeners to shifted phonetic distributions of word-initial "d" and "t" (e.g., "dill" vs. "till"), while incrementally assessing cumulative changes in listeners' perception. We use Bayesian mixed-effects psychometric models to characterize these changes, and compare listeners' behavior against both idealized learners (ideal observers that know the exposure statistics) and a model of adaptive speech perception (ideal adaptors that have to infer those statistics). We find that a distributional learning model provides a good qualitative and quantitative fit (R2>96%) to both listeners' prior perception and changes in their perception depending on the amount and type of exposure. We do, however, also identify previously unrecognized constraints on adaptivity that are unexpected under any existing model of adaptive speech perception: changes in listeners' perception seem to plateau below the level expected under successful learning.
Mind perception - the inference of mind in others - is foundational for social cognition and interaction, but previous research on its underlying dimensions has so far only produced mixed findings. In a prominent study, H.M. Gray et al. (2007) identified two dimensions of mind perception - Agency and Experience -, while more recent work instead suggests three dimensions similar to Body, Heart, and Mind (Malle, 2019; Weisman et al., 2017). Here, we provide a comprehensive account that can accommodate both dimensional structures by distinguishing target- from perceiver-specific dimensions of mind perception. These dimensions explain target- and perceiver-specific differences in mind perception that were differentially focused on by previous studies ascribing to the competing dimensional structures. To test our account empirically and compare target- vs. perceiver-specific dimensions, we gathered online survey data from two samples (N = 157, and N = 150). In both samples, exploratory factor analyses yielded two target-specific dimensions in line with Agency-Experience, and three perceiver-specific dimensions in line with Body-Heart-Mind, thereby validating our explanatory account. Further analyses showed that perceiver-specific dimensions are meaningfully associated with perceivers' demographics, personality, and spiritual belief; and that they depend on target context. Together, our results resolve inconsistencies in mind perception research and work toward a novel unifying mind perception framework.

