How the Demands of a Variable Environment Give Rise to Statistical Learning

Abstract

Language inherently requires learners to process variability in the input, as no two utterances, sentences, or speakers sound identical. Statistical learning, the ability to identify structure in the input by detecting regular patterns, is a potential mechanism that may help infants and adults cope with, and benefit from, the variability in linguistic input. In this chapter, I provide an overview of statistical learning phenomena, including identifying units (such as words) from the co-occurrence of sounds and discovering category membership from the frequency and variability of exemplars in the input. While there are many different statistical learning tasks, I propose that they share many commonalities that can be explained by viewing statistical learning as an emergent property of the way that information is stored, accessed, and integrated in memory. This perspective makes novel predictions about the process of language development and how it is related to more domain-general cognitive processes.