Numerous studies over the past decade support the claim that infants are equipped with powerful statistical language learning mechanisms. The primary evidence for statistical language learning in word segmentation comes from studies using artificial languages, continuous streams of synthesized syllables that are highly simplified relative to real speech. To what extent can these conclusions be scaled up to natural language learning? In the current experiments, English-learning 8-month-old infants’ ability to track transitional probabilities in fluent infant-directed Italian speech was tested (N = 72). The results suggest that infants are sensitive to transitional probability cues in unfamiliar natural language stimuli, and support the claim that statistical learning is sufficiently robust to support aspects of real-world language acquisition.

Numerous recent studies suggest that human learners, including both infants and adults, readily track sequential statistics computed between adjacent elements. One such statistic, transitional probability, is typically calculated as the likelihood that one element predicts another. However, little is known about whether listeners are sensitive to the directionality of this computation. To address this issue, we tested 8-month-old infants in a word segmentation task, using fluent speech drawn from an unfamiliar natural language. Critically, test items were distinguished solely by their backward transitional probabilities. The results provide the first evidence that infants track backward statistics in fluent speech.Language comprehension relies on the identification of basic lexical units. Preverbal infants quickly begin to recognize word-like sequences presented in fluent speech (Jusczyk & Aslin, 1995), suggesting that there must be some set of reliable cues marking word boundaries in the speech signal. Indeed, infants are sensitive to numerous acoustic and phonological properties correlated with word boundaries (for a recent review, see Saffran, Werker, & Werner, 2006).In particular, infants' sensitivity to transitional probability (TP), the probability of event Y given event X, has received a great deal of attention (e.g., Aslin, Saffran, & Newport, 1998;Saffran, Aslin, & Newport, 1996;Saffran, Johnson, Newport, & Aslin, 1999). TP is typically calculated according to Equation 1:On this construal, the frequency of the first element in the pair, X, is normalized as a function of its overall frequency in the corpus. TP is thus a measure of the strength with which X predicts Y. Analyses of infant-directed speech corpora suggest that TP cues could, in principle, help infants find word boundaries, at least when acting in concert with other cues (Swingley, 2005). Furthermore, infants track TPs when exposed to a synthetic speech stream drawn from a miniature artificial language, in which TP is the only available cue to word boundaries (Aslin et al., 1998;Graf Estes, Evans, Alibali, & Saffran, 2007). Infants can also track TPs in natural speech drawn from an unfamiliar language, Italian (Pelucchi, Hay, & Saffran, 2009).© 2009 Elsevier B.V. All rights reserved. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptCognition. Author manuscript; available in PMC 2010 November 1. Despite this emerging body of work, remarkably little is known about the computational underpinnings of these findings. In particular, it is not clear whether infants co...

The processes of infant word segmentation and infant word learning have largely been studied separately. However, the ease with which potential word forms are segmented from fluent speech seems likely to influence subsequent mappings between words and their referents. To explore this process, we tested the link between the statistical coherence of sequences presented in fluent speech and infants’ subsequent use of those sequences as labels for novel objects. Notably, the materials were drawn from a natural language unfamiliar to the infants (Italian). The results of three experiments suggest that there is a close relationship between the statistics of the speech stream and subsequent mapping of labels to referents. Mapping was facilitated when the labels contained high transitional probabilities in the forward and/or backward direction (Experiment 1). When no transitional probability information was available (Experiment 2), or when the internal transitional probabilities of the labels were low in both directions (Experiment 3), infants failed to link the labels to their referents. Word learning appears to be strongly influenced by infants’ prior experience with the distribution of sounds that make up words in natural languages.