# Exploring phonological complexity in statistical learning of artificial words

## TL;DR

This study found that exposure to complex speech patterns does not improve learning or generalization of artificial words in a statistical learning task.

## Contribution

The study investigates whether phonological complexity influences statistical learning of artificial words, providing new insights into auditory word learning mechanisms.

## Key findings

- Exposure to complex speech patterns did not enhance wordlikeness ratings for previously heard items.
- No reliable effects of induction condition or stimulus complexity were observed in generalization tasks.
- Participants showed sensitivity to exposure but not to complexity in artificial word learning.

## Abstract

This study examined whether phonological complexity enhances auditory word learning within a statistical learning framework. Specifically, we tested if exposure to phonologically complex speech patterns (i.e., marked consonant clusters) facilitates the segmentation and generalization of both complex and simple artificial words.

Seventy-eight adults were randomly assigned to either a complex or simple pattern induction group and exposed to bisyllabic artificial words varying in onset complexity. Participants then heard an auditory stream containing both complex and simple words, followed by a wordlikeness rating task assessing both previously heard and novel items.

Exposure to complex speech patterns did not enhance wordlikeness ratings for either previously heard (stream) or novel (generalization) artificial words. Wordlikeness ratings were significantly higher for stream items than for generalization items, indicating sensitivity to exposure, but no reliable effects of induction condition or stimulus complexity were observed.

Findings suggest that passive exposure to complex patterns does not enhance generalization within a statistical learning paradigm.