Probing the link between vision and language in material perception using psychophysics and unsupervised learning.

ABSTRACT: We can visually discriminate and recognize a wide range of materials. Meanwhile, we use language to describe what we see and communicate relevant information about the materials. Here, we investigate the relationship between visual judgment and language expression to understand how visual features relate to semantic representations in human cognition. We use deep generative models to generate images of realistic materials. Interpolating between the generative models enables us to systematically create material appearances in both well-defined and ambiguous categories. Using these stimuli, we compared the representations of materials from two behavioral tasks: visual material similarity judgments and free-form verbal descriptions. Our findings reveal a moderate but significant correlation b

SUBMITTER: Liao C 

PROVIDER: S-EPMC11478833 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature