Infants are adept at tracking statistical regularities to segment words in continuous speech. Researchers have documented infants'learning abilities using highly simplified artificial languages as speech input. However, natural language is replete with variability. Infants listening to speech encounter different speakers, different word lengths, and numerous other dimensions of complexity. The proposed experiments will use speech that captures key aspects of the natural variation observed in infants'language environments to test whether infants use statistical learning mechanisms in identifying word boundaries. This research will provide a rigorous test of whether statistical learning is in fact linked to early language acquisition.
Specific Aim 1 is to examine how infants segment words given variability in utterance types-specifically, the presence of both continuous speech and isolated words. A preliminary study showed that isolated words enhance infants'attention to statistical regularities in fluent, natural speech. Experiment 1 will test the hypothesis that hearing words in isolation helps infants discover other words in continuous speech. Experiment 2 will explore word segmentation given variation in voices, testing whether isolated words enhance statistical learning when speech comes from multiple talkers.
Specific Aim 2 is to investigate how variability in language experience influences infants'subsequent detection of statistical regularities in fluent speech. In Experiment 3, infants will first receive brief laboratory exposure to novel isolated words. This pre-familiarization is expected to constrain infants'abilities to establish word boundaries in continuous speech. Experiment 4 will test whether cross-linguistic differences in the proportion of multisyllabic words in infant-directed speech shape infants'word segmentation abilities. Spanish-learning infants, who hear far more multisyllabic words than English-learning infants over the first year, are expected to show greater facility in segmenting trisyllabic words from continuous speech than English-learning infants. The results will assess the degree to which previous learning leads to expectations that facilitate processing future speech, or whether infants'computational abilities operate continuously at each moment in time. The outcomes of these studies will inform future research exploring statistical learning abilities in young children with emergent language impairments.

Public Health Relevance

The goal of this research is to understand how typically developing infants discover structure in the complex speech they hear from caregivers. Future studies will use these tasks to assess language learning in children exhibiting difficulties with language (e.g., children at risk for specific language impairment, children with emergent autism spectrum disorder, or deaf children with cochlear implants). The eventual goals are to investigate whether the mechanisms responsible for learning are compromised in these clinical populations, and to develop more appropriate tools for early diagnosis and intervention.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F12A-E (20))
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Mccardle, Peggy D
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University of Wisconsin Madison
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United States
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Estes, Katharine Graf; Lew-Williams, Casey (2015) Listening through voices: Infant statistical word segmentation across multiple speakers. Dev Psychol 51:1517-28
Lew-Williams, Casey; Saffran, Jenny R (2012) All words are not created equal: expectations about word length guide infant statistical learning. Cognition 122:241-6
Lew-Williams, Casey; Pelucchi, Bruna; Saffran, Jenny R (2011) Isolated words enhance statistical language learning in infancy. Dev Sci 14:1323-9