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This research investigates the development of constraints in word learning. Previous experiments have shown that as infants gain more knowledge of native language structure, they become more selective about the forms that they accept as labels. However, the developmental pattern exhibited depends greatly on the way that infants are introduced to the labels and tested. In a series of experiments, we examined how providing referential context in the form of familiar objects and familiar object names affects how infants learn labels that they would otherwise reject, nonspeech sounds. We found evidence of the development of intersecting constraints: Younger infants (14-month-olds) were more open to learning nonspeech tone labels than older infants (19-month-olds), and younger infants were more open to the influence of referential context. These findings suggest that infants form expectations about labels and labeling contexts as they become more sophisticated learners.

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Infants are adept at learning statistical regularities in artificial language materials, suggesting that the ability to learn statistical structure may support language development. Indeed, infants who perform better on statistical learning tasks tend to be more advanced in parental reports of infants' language skills. Work with adults suggests that one way statistical learning ability affects language proficiency is by facilitating real-time language processing. Here we tested whether 15-month-olds' ability to learn sequential statistical structure in artificial language materials is related to their ability to encode and interpret native-language speech. Specifically, we tested their ability to learn sequential structure among syllables (Experiment 1) and words (Experiment 2), as well as their ability to encode familiar English words in sentences. The results suggest that infants' ability to learn sequential structure among syllables is related to their lexical-processing efficiency, providing continuity with findings from children and adults, though effects were modest.

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To learn from their environments, infants must detect structure behind pervasive variation. This presents substantial and largely untested learning challenges in early language acquisition. The current experiments address whether infants can use statistical learning mechanisms to segment words when the speech signal contains acoustic variation produced by changes in speakers' voices. In Experiment 1, 8- and 10-month-old infants listened to a continuous stream of novel words produced by 8 different female voices. The voices alternated frequently, potentially interrupting infants' detection of transitional probability patterns that mark word boundaries. Infants at both ages successfully segmented words in the speech stream. In Experiment 2, 8-month-olds demonstrated the ability to generalize their learning about the speech stream when presented with a new, acoustically distinct voice during testing. However, in Experiments 3 and 4, when the same speech stream was produced by only 2 female voices, infants failed to segment the words. The results of these experiments indicate that low acoustic variation may interfere with infants' efficiency in segmenting words from continuous speech, but that infants successfully use statistical cues to segment words in conditions of high acoustic variation. These findings contribute to our understanding of whether statistical learning mechanisms can scale up to meet the demands of natural learning environments.

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The present experiments tested bilingual infants' developmental narrowing for the interpretation of sounds that form words. These studies addressed how language specialization proceeds when the environment provides varied and divergent input. Experiment 1 (N = 32) demonstrated that bilingual 14- and 19-month-olds learned a pair of object labels consisting of the same syllable produced with distinct pitch contours (rising and falling). Infants' native languages did not use pitch contour to differentiate words. In Experiment 2 (N = 16), 22-month-old bilinguals failed to learn the labels. These results conflict with the developmental trajectory of monolinguals, who fail to learn pitch contour contrasts as labels at 17-19 months (Hay, Graf Estes, Wang, & Saffran, 2015). Bilingual infants exhibited a prolonged period of flexibility in their interpretation of potential word forms.

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Adults typically use an exaggerated, distinctive speaking style when addressing infants. However, the effects of infant-directed (ID) speech on infants' learning is not yet well understood. This research investigates how ID speech affects how infants perform a key function in language acquisition, associating the sounds of words with their meanings. Seventeen-month-old infants were presented with two label-object pairs in a habituation-based word learning task. In Experiment 1, the labels were produced in adult-directed (AD) speech. In Experiment 2, the labels were produced in ID prosody; they had higher pitch, greater pitch variation, and longer durations than the AD labels. We found that infants failed to learn the labels in AD speech, but succeeded in learning the same labels when they were produced in ID speech. Experiment 3 investigated the role of variability in learning from ID speech. When the labels were presented in ID prosody with no variation across tokens, infants failed to learn them. Our findings indicate that ID prosody can affect how readily infants map sounds to meanings and that the variability in prosody that is characteristic of ID speech may play a key role in its effect on learning new words.

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Many studies have shown that listeners can segment words from running speech based on conditional probabilities of syllable transitions, suggesting that this statistical learning could be a foundational component of language learning. However, few studies have shown a direct link between statistical segmentation and word learning. We examined this possible link in adults by following a statistical segmentation exposure phase with an artificial lexicon learning phase. Participants were able to learn all novel object-label pairings, but pairings were learned faster when labels contained high probability (word-like) or non-occurring syllable transitions from the statistical segmentation phase than when they contained low probability (boundary-straddling) syllable transitions. This suggests that, for adults, labels inconsistent with expectations based on statistical learning are harder to learn than consistent or neutral labels. In contrast, a previous study found that infants learn consistent labels, but not inconsistent or neutral labels.

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