Acoustic parameter combinations underlying mapping of pseudoword sounds to multiple domains of meaning: Representational similarity analyses and machine-learning models.

ABSTRACT: In spoken language, iconicity, referring to the resemblance between the sound structure of words and their meaning, is often studied using pseudowords. Previously, we showed that representational dissimilarity matrices (RDMs) of the shape ratings of pseudowords correlated significantly with RDMs of acoustic parameters reflecting spectro-temporal variations; the ratings also correlated significantly with voice quality parameters. Here, we examined how perceptual ratings relate to these parameters of pseudowords across eight meaning domains. We largely replicated our previous findings for shape, while observing different patterns for other domains. Using a k-nearest-neighbor (KNN) machine-learning algorithm, we compared 4095 combinations of 12 acoustic parameters (three spectro-temporal and

SUBMITTER: Kumar GV 

PROVIDER: S-EPMC12752017 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature