On humans' (explicit) intuitions about the meaning of novel words

Abstract

Pseudowords offer a unique opportunity to investigate how humans deal with new (verbal) information. Within this framework, previous studies have shown that, at the implicit level, humans exploit systematic associations in the form-meaning interface to process new information by relying on (sub-lexical) contents already mapped in semantic memory. However, whether speakers exploit such processes in explicit decisions about the meanings elicited by unfamiliar terms remains an open, important question. Here, we tested this by leveraging computational models that are able to induce semantic representations for out-of-vocabulary stimuli. Across two experiments, we demonstrate that participants' guesses about pseudoword meanings in a 2AFC task consistently align with the model's predictions. This indicates that humans' ability to extract meaningful knowledge from complex statistical patterns can affect explicit decisions.