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The specificity of sequential statistical learning: Statistical learning accumulates predictive information from unstructured input but is dissociable from (declarative) memory for words

Endress, A. ORCID: 0000-0003-4086-5167 (2024). The specificity of sequential statistical learning: Statistical learning accumulates predictive information from unstructured input but is dissociable from (declarative) memory for words. Cognition,

Abstract

Learning statistical regularities from the environment is ubiquitous across domains and species. It might support the earliest stages of language acquisition, especially identifying and learning words from fluent speech (i.e., wordsegmentation). But how do the statistical learning mechanisms involved in word-segmentation interact with the memory mechanisms needed to actually remember words as well as with the learning situations where words actually need to be learned? We show that, in a memory recall task after exposure to continuous, statistically structured speech sequences, participants track the statistical structure of the speech sequences and are thus sensitive to probable syllable transitions, but hardly remember any items at all. Analysis of their productions suggests that they are unable to identify probable word boundaries. As a result, they tend to produce low-probability items even while preferring high-probability items in a recognition test. Only discrete familiarization sequences with isolated words yield memories of actual items. Through computational modeling, we show that earlier results purportedly supporting memory-based theories of statistical learning can be reproduced by memoryless Hebbian learning mechanisms. Turning to how specific learning situations affect statistical learning, we show that it predominantly operates in continuous speech sequences like those used in earlier experiments, but not in discrete chunk sequences likely encountered during language acquisition. Taken together, these results suggest that statistical learning might be specialized to accumulate distributional information, but that it is dissociable from the (declarative) memory mechanisms needed to acquire words and does not allow learners to identify probably word boundaries.

Publication Type: Article
Additional Information: © 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: Statistical Learning; Declarative Memory; Predictive Processing; Language Acquisition; Hebbian Learning
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > QA Mathematics
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Departments: School of Health & Psychological Sciences
School of Health & Psychological Sciences > Psychology
SWORD Depositor:
[thumbnail of segm_recall_main_final_jou.pdf] Text - Accepted Version
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Available under License Creative Commons Attribution Non-commercial No Derivatives.

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