Premium
Do Infants Learn Words From Statistics? Evidence From English‐Learning Infants Hearing Italian
Author(s) -
Shoaib Amber,
Wang Tianlin,
Hay Jessica F.,
Lany Jill
Publication year - 2018
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1111/cogs.12673
Subject(s) - referent , object (grammar) , psychology , linguistics , natural language processing , statistical learning , text segmentation , language acquisition , artificial intelligence , lexical item , word (group theory) , vocabulary , computer science , segmentation , philosophy , mathematics education
Infants are sensitive to statistical regularities (i.e., transitional probabilities, or TP s) relevant to segmenting words in fluent speech. However, there is debate about whether tracking TP s results in representations of possible words. Infants show preferential learning of sequences with high TP s ( HTP s) as object labels relative to those with low TP s ( LTP s). Such findings could mean that only the HTP sequences have a word‐like status, and they are more readily mapped to a referent for that reason. But these findings could also suggest that HTP sequences are easier to encode, just like any other predictable sequence. Here we aimed to distinguish between these explanations. To do so, we built on findings that infants become resistant to learning labels that are not typical of their native language as they approach 2 years of age and add words to their lexicons. If tracking TP s in speech results in identifying candidate words, at this age TP s may have reduced power to confer lexical status when they yield a unit that is very dissimilar to word forms that are typical of infants’ native language. Indeed, we found that at 20 months, English‐learning infants with relatively small vocabularies learned HTP Italian words (but not LTP words) as object labels, while infants with larger vocabularies resisted learning HTP Italian words. These findings suggest that the HTP sequences may be represented as candidate words, and more broadly, that TP statistics are relevant to word learning.