The acquisition of language is a daunting task for infants. Research on this process provides an opportunity to address central issues related to the early development of human cognition. This application focuses on statistical language learning mechanisms that detect linguistic units by tracking input patterns of sounds. Recent research suggests that infant learners possess statistical learning mechanisms that may play an important role in language acquisition. Still unknown is the way in which these mechanisms interact to derive linguistic structure, given multiple possibilities. The proposed research addresses these issues by posing the following questions: (1) Can infants perform multiple analyses of the same set of input subsequently, so that the output of one set of statistical computations is the input to the next analysis, and simultaneously, such that multiple levels are processed at once? What factors determine which analysis emerges as the output of the learning process? (2) Do similar constraints on learning, with respect to acoustic and statistical structure, govern statistical language learning by adults, children, and infants? (3) Are the statistical learning mechanisms investigated in (1)-(2) tailored specifically for language learning, or can they operate on stimuli drawn from other domains? These questions will be addressed using previously developed laboratory learning paradigms which permit careful manipulation of the input. The answers to these questions will inform an emerging theoretical framework, constrained statistical learning, intended to elucidate the study of language acquisition and other pressing issues in human learning and development.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
1R01HD037466-01A1
Application #
6128848
Study Section
Special Emphasis Panel (ZRG1-BBBP-3 (01))
Program Officer
Mccardle, Peggy D
Project Start
2000-08-01
Project End
2004-07-31
Budget Start
2000-08-01
Budget End
2001-07-31
Support Year
1
Fiscal Year
2000
Total Cost
$103,450
Indirect Cost
Name
University of Wisconsin Madison
Department
Pediatrics
Type
Other Domestic Higher Education
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Benitez, Viridiana L; Saffran, Jenny R (2018) Predictable Events Enhance Word Learning in Toddlers. Curr Biol 28:2787-2793.e4
Potter, Christine E; Wang, Tianlin; Saffran, Jenny R (2017) Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials. Cogn Sci 41 Suppl 4:913-927
Willits, Jon A; Seidenberg, Mark S; Saffran, Jenny R (2014) Distributional structure in language: contributions to noun-verb difficulty differences in infant word recognition. Cognition 132:429-36
Lany, Jill (2014) Judging words by their covers and the company they keep: probabilistic cues support word learning. Child Dev 85:1727-39
Romberg, Alexa R; Saffran, Jenny R (2013) All together now: concurrent learning of multiple structures in an artificial language. Cogn Sci 37:1290-320
Willits, Jon A; Wojcik, Erica H; Seidenberg, Mark S et al. (2013) Toddlers Activate Lexical Semantic Knowledge in the Absence of Visual Referents: Evidence from Auditory Priming. Infancy 18:
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
Romberg, Alexa R; Saffran, Jenny R (2012) Expectancy learning from probabilistic input by infants. Front Psychol 3:610
Hay, Jessica F; Saffran, Jenny R (2012) Rhythmic grouping biases constrain infant statistical learning. Infancy 17:610-641
Lany, Jill; Saffran, Jenny R (2011) Interactions between statistical and semantic information in infant language development. Dev Sci 14:1207-19

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