Artificial language studies have demonstrated that learners are able to segment individual
word-like units from running speech using the transitional probability information. However,
this skill has rarely been examined in the context of natural languages, where stimulus
parameters can be quite different. In this study, two groups of English-speaking learners
were exposed to Norwegian sentences over the course of three fMRI scans. One group was
provided with input in which transitional probabilities predicted the presence of target words …