# Beyond the statistics: Questioning the arbitrariess of the "words" in statistical learning paradigms

- Lauren Emberson,
*Cornell University, *
- Jason Zevin,
*Cornell University*

## Abstract

Statistical learning is a form of implicit, unsupervised learning
related to complex visual processing and language development. Statistical
learning studies are often designed as if all stimuli of a certain type (e.g.
CVCs) bound by statistical regularities should be learned equally well, implying
that statistical learning occurs via an abstract mechanism. We conducted a series
of 12 statistical learning experiments using the same set of 15 auditory CVCs in
different statistically-bound "words" (triplets of CVCs). After being exposed to
"words" 36 times each in random order, participants were tested for learning.
Surprisingly, we only found learning in 7 of the 12 groups. Since all
combinations of CVCs are not learned equally well even though the transitional
probabilities are equivalent, these results indicate that CVCs influence
statistical learning. We examine these results in relation to regularities in the
ambient language and specific phonological qualities of the "words" formed.

Back to Friday Posters