Learners rely on a combination of experience-independent and experience-dependent mechanisms to extract information from the environment. Language acquisition involves both types of mechanisms, but most theorists emphasize the relative importance of experience-independent mechanisms. The present study shows that a fundamental task of language acquisition, segmentation of words from fluent speech, can be accomplished by 8-month-old infants based solely on the statistical relationships between neighboring speech sounds. Moreover, this word segmentation was based on statistical learning from only 2 minutes of exposure, suggesting that infants have access to a powerful mechanism for the computation of statistical properties of the language input.

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A recent report demonstrated that 8-month-olds can segment a continuous stream of speech syllables, containing no acoustic or prosodic cues to word boundaries, into wordlike units after only 2 min of listening experience (Saffran, Aslin, & Newport, 1996). Thus, a powerful learning mechanism capable of extracting statistical information from fluent speech is available early in development. The present study extends these results by documenting the particular type of statistical computation—transitional (conditional) probability—used by infants to solve this word-segmentation task. An artificial language corpus, consisting of a continuous stream of trisyllabic nonsense words, was presented to 8-month-olds for 3 min. A postfamiliarization test compared the infants' responses to words versus part-words (trisyllabic sequences spanning word boundaries). The corpus was constructed so that test words and part-words were matched in frequency, but differed in their transitional probabilities. Infants showed reliable discrimination of words from part-words, thereby demonstrating rapid segmentation of continuous speech into words on the basis of transitional probabilities of syllable pairs.

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This paper suggests that there are constraints on learning required to explain the acquisition of language, in particular, mafuratlonal constraints. First, empirical evidence for this claim is reviewed. The evidence from several studies of both first and second language acquisition suggests that normal language learning occurs only when exposure to the language begins early in life. With exposure beginning later in life, asymptotic performance in the language declines: the effects over age of first exposure are approximately linear through childhood, with a flattening of the function in adulthood. These outcomes argue that some type of constraints ensuring successful language learning exist early in life, and weaken with increosing maturation. Second, two hypotheses are considered as to the nature of these maturational changes. One hypothesis is that constraints on learning particular to language acquisition undergo maturational decay. A second hypothesis, which is considered in more detail, suggests that language learning abilities decline because of the expansion of nonlinguistic cognitive abilities.

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Two experiments investigated the performance of first-grade children and adults on an incidental language-learning task. Learning entailed word segmentation from continuous speech, an initial and crucial component of language acquisition. Subjects were briefly exposed to an unsegmented artificial language, presented auditorily, in which the only cues to word boundaries were the transitional probabilities between syllables. Subjects were not told that they were listening to a language, or even to listen at all; rather, they were engaged in a cover task of creating computer illustrations. Both adults and children learned the words of the language. Moreover, the children performed as well as the adults. These data suggest that a statistical learning mechanism (transitional probability computation) is able to operate incidentally and, surprisingly, as well in children as in adults.