From Tracking Statistics to Learning words: Statistical Learning and Lexical Acquisition

Abstract

By age 1, infants display remarkable sensitivity to the sound structure of their native language. Statistical learning, the process of detecting structure in the environment by tracking patterns in the input, is hypothesized to contribute to infants’ early learning about sound. The present paper explores how infants’ ability to track distributional information in the speech signal contributes to a fundamental aspect of language development, linking sounds with meanings in word learning. Previous research has demonstrated that infants detect several cues that mark where words begin and end in the fluent stream of speech (e.g., transitional probability, phonotactic regularities). Tracking such patterns may allow infants to isolate individual words, making them available to be associated with referents. Even very early in vocabulary development, statistical learning about which sound sequences are likely or unlikely to occur within words in the native language may also shape word learning. We propose that early experience with sound sequence regularities provides infants with a foundation for lexical acquisition.