TY - JOUR
T1 - Fine-grained sensitivity to statistical information in adult word learning
AU - Vouloumanos, Athena
N1 - Funding Information:
This work was supported by funding from the Canadian Institutes of Health Research, the Natural Sciences and Engineering Research Council (NSERC) of Canada, and the Fonds québécois de la recherche sur la société et la culture to the author, and funding from NSERC and the Human Frontier Science Program to Janet Werker. I am especially grateful to Janet Werker without whom this work would not have been possible, and Gary Marcus and Kris Onishi for crucial discussions and comments on previous drafts. My thanks to Katherine Yoshida and Miguel Imperial, as well as Karla Kaun, Alisa Almas, Marisa Cruickshank, Michael Vitevitch, Rhonda Amsel, Jesse Snedeker, and Alia Martin for their contributions to this research.
PY - 2008/5
Y1 - 2008/5
N2 - A language learner trying to acquire a new word must often sift through many potential relations between particular words and their possible meanings. In principle, statistical information about the distribution of those mappings could serve as one important source of data, but little is known about whether learners can in fact track multiple word-referent mappings, and, if they do, the precision with which they can represent those statistics. To test this, two experiments contrasted a pair of possibilities: that learners encode the fine-grained statistics of mappings in the input - both high- and low-frequency mappings - or, alternatively, that only high frequency mappings are represented. Participants were briefly trained on novel word-novel object pairs combined with varying frequencies: some objects were paired with one word, other objects with multiple words with differing frequencies (ranging from 10% to 80%). Results showed that participants were exquisitely sensitive to very small statistical differences in mappings. The second experiment showed that word learners' representation of low frequency mappings is modulated as a function of the variability in the environment. Implications for Mutual Exclusivity and Bayesian accounts of word learning are discussed.
AB - A language learner trying to acquire a new word must often sift through many potential relations between particular words and their possible meanings. In principle, statistical information about the distribution of those mappings could serve as one important source of data, but little is known about whether learners can in fact track multiple word-referent mappings, and, if they do, the precision with which they can represent those statistics. To test this, two experiments contrasted a pair of possibilities: that learners encode the fine-grained statistics of mappings in the input - both high- and low-frequency mappings - or, alternatively, that only high frequency mappings are represented. Participants were briefly trained on novel word-novel object pairs combined with varying frequencies: some objects were paired with one word, other objects with multiple words with differing frequencies (ranging from 10% to 80%). Results showed that participants were exquisitely sensitive to very small statistical differences in mappings. The second experiment showed that word learners' representation of low frequency mappings is modulated as a function of the variability in the environment. Implications for Mutual Exclusivity and Bayesian accounts of word learning are discussed.
KW - Adults
KW - Constraints
KW - Language acquisition
KW - Statistical learning
KW - Word learning
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U2 - 10.1016/j.cognition.2007.08.007
DO - 10.1016/j.cognition.2007.08.007
M3 - Article
C2 - 17950721
AN - SCOPUS:41349100680
SN - 0010-0277
VL - 107
SP - 729
EP - 742
JO - Cognition
JF - Cognition
IS - 2
ER -