All together now: concurrent learning of multiple structures in an artificial language.

TitleAll together now: concurrent learning of multiple structures in an artificial language.
Publication TypeJournal Article
Year of Publication2013
AuthorsRomberg AR, Saffran JR
JournalCogn Sci
Volume37
Start Page1290
Issue7
Pagination1290-320
Date Published2013 Sep-Oct
Type of ArticleCase Study
ISBN Number12345678
ISSN1551-6709
Accession Number987654321
Call Number555-8675309
Other Numbersyes
KeywordsAdult, Female, Humans, Language, Language Development, Learning, Male, Psycholinguistics
Abstract

Natural languages contain many layers of sequential structure, from the distribution of phonemes within words to the distribution of phrases within utterances. However, most research modeling language acquisition using artificial languages has focused on only one type of distributional structure at a time. In two experiments, we investigated adult learning of an artificial language that contains dependencies between both adjacent and non-adjacent words. We found that learners rapidly acquired both types of regularities and that the strength of the adjacent statistics influenced learning of both adjacent and non-adjacent dependencies. Additionally, though accuracy was similar for both types of structure, participants' knowledge of the deterministic non-adjacent dependencies was more explicit than their knowledge of the probabilistic adjacent dependencies. The results are discussed in the context of current theories of statistical learning and language acquisition.

DOI10.1111/cogs.12050
Short TitleConcurrent Learning
Alternate JournalCogn Sci
Original PublicationScience
Reprint Edition2nd Edition
PubMed ID23772795
PubMed Central IDPMC3769465
Grant ListT32 HD007475 / HD / NICHD NIH HHS / United States
P30 HD003352 / HD / NICHD NIH HHS / United States
R01 HD037466 / HD / NICHD NIH HHS / United States
F31 DC99042 / DC / NIDCD NIH HHS / United States
P30HD03352 / HD / NICHD NIH HHS / United States
5T32 HD007475-17 / HD / NICHD NIH HHS / United States
F31 DC009940 / DC / NIDCD NIH HHS / United States
R37 HD037466 / HD / NICHD NIH HHS / United States