All Together Now: Concurrent Learning of Multiple Structures in an Artificial Language
Open accessAbstract
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.
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The SL task measures the ability to learn adjacent and non-adjacent relationships.
“We adopted a statistical learning task of Romberg and Saffran (2013, Experiment 1) as a linguistic measure of the ability (i.e., verbal SL) that underlies proceduralization.”
From Testing the three-stage model of second language skill acquisition (2025) · cites this paper as Romberg and Saffran (2013, Experiment 1)
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Testing the three-stage model of second language skill acquisition
Maie, R., & Godfroid, A. (2025) · Studies in Second Language Acquisition · doi:10.1017/s027226312500021x · Cited by 5 · see citing works
- Authors
- Romberg, A. R., & Saffran, J. R.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Romberg, Alexa R.
- ORCID
- Saffran, Jenny R.
- Venue
- Cognitive Science
- Publisher
- Wiley
- Published
- 2013-06-14
- Volume
- 37
- Issue
- 7
- Pages
- 1290-1320
- ISSN
- 0364-0213 (ISSN-L)
- 1551-6709
- PMC
- PMC3769465
- OpenAlex
- W2113062646
- Cited by
- 77
- References
- 3
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 6 · 2020: 8 · 2019: 8 · 2018: 9 · 2017: 9 · 2016: 12 · 2015: 7 · 2014: 4 · 2013: 2
- FWCI
- 17.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cognitive Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- James S. McDonnell Foundation (P30HD03352)
- National Institutes of Health
- Intellectual and Developmental Disabilities Research Center (P30HD03352)
- National Institute on Deafness and Other Communication Disorders (F31 DC99042, F31DC009940)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R37HD037466, P30HD03352., R01HD037466, P30HD003352, T32HD007475)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- artificial language learning, statistical learning, language acquisition, non-adjacent dependencies, sequential structure, probabilistic dependencies, explicit knowledge, adult language learners
- MeSH terms
- Adult, Female, Humans, Language, Language Development, Learning, Male, Psycholinguistics
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