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Poster B in Poster Session B: Tuesday, August 4, 2:00 – 3:45 pm, Kimmel Center, Shorin & Rosenthal Rooms

The Role of Prior Precision and Prior Probability in Voice Perception

Carina Ufer¹, Fabian Schneider², Helen Blank³; ¹University of Medical Center Hamburg-Eppendorf, ²Universität Klinikum Eppendorf // University Hospital Eppendorf, ³University Medical Center Hamburg-Eppendorf, Ruhr University Bochum, University Alliance Ruhr

Presenter: Carina Ufer

Perception is often described as Bayesian inference, yet it remains unclear how prior precision and prior probability shape inference when multiple latent causes compete. We address this question in voice perception, where listeners infer speaker identity from variable acoustic input. Across two behavioral setups, participants learned distributions over speaker priors in a perceptual space. When prior probabilities were constant, participants preferentially attributed ambiguous stimuli to low-precision priors, aligning with normative Bayesian inference. Computational modeling further revealed that participants acquired idiosyncratic prior distributions. When prior probability of latent causes was manipulated, participants biased their inferences toward more probable causes, with stronger effects under higher cue reliability leading to faster response times. Together, these findings show that perceptual inference reflects a structured competition between probabilistic hypotheses, shaped jointly by prior precision and prior probability.

Topic Area: Auditory, Speech & Language Processing