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The role of statistical learning in language acquisition has been investigated in two experiments involving predictive dependencies in basic phrase structure. Adults and children were tested using an artificial language in which predictive dependencies provided cues to phrase structure.

The hypothesis that learners use statistical information such as predicative relationships to acquire phrase structure was examined. Participants in the study were exposed to artificial languages that contained or violated the dependencies of natural languages, and the findings indicated that the degree to which the input contained linguistic content did not affect the learning outcomes.

Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process. [ABSTRACT FROM AUTHOR]

Learning the meanings of words involves not only linking individual words to referents but also building a network of connections among entities in the world, concepts, and words. Previous studies reveal that infants and adults track the statistical co-occurrence of labels and objects across multiple ambiguous training instances to learn words. However, it is less clear whether, given distributional or attentional cues, learners also encode associations among the novel objects. We investigated the consequences of two types of cues that highlighted object-object links in a cross-situational word learning task: distributional structure – how frequently the referents of novel words occurred together – and visual context – whether the referents were seen on matching backgrounds. Across three experiments, we found that in addition to learning novel words, adults formed connections between frequently co-occurring objects. These findings indicate that learners exploit statistical regularities to form multiple types of associations during word learning. [ABSTRACT FROM AUTHOR]