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  1. Evaluating the Relative Importance of Wordhood Cues Using Statistical Learning.Elizabeth Pankratz, Simon Kirby & Jennifer Culbertson - 2024 - Cognitive Science 48 (3):e13429.
    Identifying wordlike units in language is typically done by applying a battery of criteria, though how to weight these criteria with respect to one another is currently unknown. We address this question by investigating whether certain criteria are also used as cues for learning an artificial language—if they are, then perhaps they can be relied on more as trustworthy top‐down diagnostics. The two criteria for grammatical wordhood that we consider are a unit's free mobility and its internal immutability. These criteria (...)
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  • Tuning in to non-adjacencies: Exposure to learnable patterns supports discovering otherwise difficult structures.Martin Zettersten, Christine E. Potter & Jenny R. Saffran - 2020 - Cognition 202 (C):104283.
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  • Perceptual intake explains variability in statistical word segmentation.Felix Hao Wang, Meili Luo & Suiping Wang - 2023 - Cognition 241 (C):105612.
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  • Musical instrument familiarity affects statistical learning of tone sequences.Stephen C. Van Hedger, Ingrid S. Johnsrude & Laura J. Batterink - 2022 - Cognition 218 (C):104949.
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  • How sequence learning unfolds: Insights from anticipatory eye movements.Amir Tal & Eli Vakil - 2020 - Cognition 201 (C):104291.
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  • Of words and whistles: Statistical learning operates similarly for identical sounds perceived as speech and non-speech.Sierra J. Sweet, Stephen C. Van Hedger & Laura J. Batterink - 2024 - Cognition 242 (C):105649.
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  • Learning Words While Listening to Syllables: Electrophysiological Correlates of Statistical Learning in Children and Adults.Ana Paula Soares, Francisco-Javier Gutiérrez-Domínguez, Alexandrina Lages, Helena M. Oliveira, Margarida Vasconcelos & Luis Jiménez - 2022 - Frontiers in Human Neuroscience 16.
    From an early age, exposure to a spoken language has allowed us to implicitly capture the structure underlying the succession of speech sounds in that language and to segment it into meaningful units. Statistical learning, the ability to pick up patterns in the sensory environment without intention or reinforcement, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language, including the discovery of word boundaries in the continuous acoustic stream. Although extensive evidence has (...)
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  • Explicit Instructions Do Not Enhance Auditory Statistical Learning in Children With Developmental Language Disorder: Evidence From Event-Related Potentials.Ana Paula Soares, Francisco-Javier Gutiérrez-Domínguez, Helena M. Oliveira, Alexandrina Lages, Natália Guerra, Ana Rita Pereira, David Tomé & Marisa Lousada - 2022 - Frontiers in Psychology 13.
    A current issue in psycholinguistic research is whether the language difficulties exhibited by children with developmental language disorder [DLD, previously labeled specific language impairment ] are due to deficits in their abilities to pick up patterns in the sensory environment, an ability known as statistical learning, and the extent to which explicit learning mechanisms can be used to compensate for those deficits. Studies designed to test the compensatory role of explicit learning mechanisms in children with DLD are, however, scarce, and (...)
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  • What Determines Visual Statistical Learning Performance? Insights From Information Theory.Noam Siegelman, Louisa Bogaerts & Ram Frost - 2019 - Cognitive Science 43 (12):e12803.
    In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the co‐occurrences between them are (...)
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  • Statistical Learning Is Not Age‐Invariant During Childhood: Performance Improves With Age Across Modality.Amir Shufaniya & Inbal Arnon - 2018 - Cognitive Science 42 (8):3100-3115.
    Humans are capable of extracting recurring patterns from their environment via statistical learning (SL), an ability thought to play an important role in language learning and learning more generally. While much work has examined statistical learning in infants and adults, less work has looked at the developmental trajectory of SL during childhood to see whether it is fully developed in infancy or improves with age, like many other cognitive abilities. A recent study showed modality‐based differences in the effect of age (...)
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  • Familiarity, consistency, and systematizing in morphology.R. Alexander Schumacher & Janet B. Pierrehumbert - 2021 - Cognition 212:104512.
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  • Systematicity, but not compositionality: Examining the emergence of linguistic structure in children and adults using iterated learning.Limor Raviv & Inbal Arnon - 2018 - Cognition 181 (C):160-173.
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  • Does auditory deprivation impairs statistical learning in the auditory modality?Jacques Pesnot Lerousseau, Céline Hidalgo, Stéphane Roman & Daniele Schön - 2022 - Cognition 222 (C):105009.
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  • The Role of Stimulus‐Specific Perceptual Fluency in Statistical Learning.Andrew Perfors & Evan Kidd - 2022 - Cognitive Science 46 (2):e13100.
    Cognitive Science, Volume 46, Issue 2, February 2022.
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  • The Role of Stimulus‐Specific Perceptual Fluency in Statistical Learning.Andrew Perfors & Evan Kidd - 2022 - Cognitive Science 46 (2):e13100.
    Humans have the ability to learn surprisingly complicated statistical information in a variety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here, we present experimental work suggesting that at least some individual differences arise from stimulus-specific variation in perceptual fluency: the ability to rapidly or (...)
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  • Implicit Statistical Learning Across Modalities and Its Relationship With Reading in Childhood.Elpis V. Pavlidou & Louisa Bogaerts - 2019 - Frontiers in Psychology 10.
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  • Visual statistical learning is facilitated in Zipfian distributions.Ori Lavi-Rotbain & Inbal Arnon - 2021 - Cognition 206 (C):104492.
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  • Statistical Learning of Language: A Meta‐Analysis Into 25 Years of Research.Erin S. Isbilen & Morten H. Christiansen - 2022 - Cognitive Science 46 (9):e13198.
    Cognitive Science, Volume 46, Issue 9, September 2022.
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  • Individual Differences in Verb Bias Sensitivity in Children and Adults With Developmental Language Disorder.Jessica E. Hall, Amanda Owen Van Horne & Thomas A. Farmer - 2019 - Frontiers in Human Neuroscience 13.
  • Syllabic rhythm and prior linguistic knowledge interact with individual differences to modulate phonological statistical learning.Ireri Gómez Varela, Joan Orpella, David Poeppel, Pablo Ripolles & M. Florencia Assaneo - 2024 - Cognition 245 (C):105737.
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  • When the “Tabula” is Anything but “Rasa:” What Determines Performance in the Auditory Statistical Learning Task?Amit Elazar, Raquel G. Alhama, Louisa Bogaerts, Noam Siegelman, Cristina Baus & Ram Frost - 2022 - Cognitive Science 46 (2):e13102.
    Cognitive Science, Volume 46, Issue 2, February 2022.
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  • Statistical Learning, Implicit Learning, and First Language Acquisition: A Critical Evaluation of Two Developmental Predictions.Inbal Arnon - 2019 - Topics in Cognitive Science 11 (3):504-519.
    In this article, Arnon explores the link between implicit learning, statistical learning and language development. She focuses on two central themes, namely the issue of age invariance and the question of variation in learning outcomes. Arnon suggests that the two literatures are studying a fundamentally similar phenomenon and argues in favor of a closer alignment. However, she also raises important methodological concerns.
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