Source Paper
Exploring phonological complexity in statistical learning of artificial words
Maggu AR, Overath T
PLoS One • 2026
Wordlikeness Testing
Objective: To assess participants' gradient judgments of wordlikeness based on statistical learning from pattern induction and word segmentation exposure
This is a Wordlikeness Testing protocol using Human as the model organism. The procedure involves 3 procedural steps, 6 equipment items, 2 materials. Extracted from a 2026 paper published in PLoS One.
Model and subjects
Human • N/A • 15 males, 63 females • 20.47 years (SD: 3.21) • 78
Study window
~1 minutes hands-on
Core workflow
Pattern Induction • Word Segmentation • Wordlikeness Testing
Primary readouts
- 7-point Likert scale wordlikeness ratings (1 = least likely, 7 = most likely to be a word)
Key equipment and reagents
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Protocol Steps
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Pattern Induction
Participants randomly allocated to Complex (n=39) or Simple (n=39) pattern groups. Complex group exposed to 30 bisyllabic stimuli with clusters, Simple group to 30 stimuli with plosives/fricatives. Each stimulus 600ms with 2s inter-stimulus interval.
View evidence from paper
“Participants in the Complex pattern group were exposed to the 30 bisyllabic speech stimuli with clusters (i.e., complex stimuli) in the initial position”
Word Segmentation
All participants listen to auditory stream containing 4 artificial words (2 complex clusters, 2 simple), randomly repeated 26 times each for total of 104 presentations.
View evidence from paper
“These four stimuli were randomly repeated 26 times each, leading to a total of 104 stimuli presentations over a duration of 1 min and 12 secs”
Wordlikeness Testing
All participants rate 8 artificial words (4 from segmentation stage, 4 novel) on 7-point Likert scale for wordlikeness. 4 simple and 4 complex words total. Each word played twice in randomized order.
View evidence from paper
“participants were asked to rate the stimuli in this stage on a 7-point Likert scale in terms of their wordlikeness (based on their exposure so far), with 1 being "least likely" and 7 being "most likely" a 'word'”