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  1. The Role of Feedback in the Statistical Learning of Language‐Like Regularities.Felicity F. Frinsel, Fabio Trecca & Morten H. Christiansen - 2024 - Cognitive Science 48 (3):e13419.
    In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab‐based experiments, using artificial languages, many of the cues and features that are part of real‐world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language‐like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in (...)
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  • The Interplay of Cross‐Situational Word Learning and Sentence‐Level Constraints.Judith Koehne & Matthew W. Crocker - 2015 - Cognitive Science 39 (5):849-889.
    A variety of mechanisms contribute to word learning. Learners can track co-occurring words and referents across situations in a bottom-up manner. Equally, they can exploit sentential contexts, relying on top–down information such as verb–argument relations and world knowledge, offering immediate constraints on meaning. When combined, CSWL and SLCL potentially modulate each other's influence, revealing how word learners deal with multiple mechanisms simultaneously: Do they use all mechanisms? Prefer one? Is their strategy context dependent? Three experiments conducted with adult learners reveal (...)
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  • When Meaning Is Not Enough: Distributional and Semantic Cues to Word Categorization in Child Directed Speech.Feijoo Sara, Muñoz Carmen, Amadó Anna & Serrat Elisabet - 2017 - Frontiers in Psychology 8.
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  • Learning vocabulary and grammar from cross-situational statistics.Patrick Rebuschat, Padraic Monaghan & Christine Schoetensack - 2021 - Cognition 206 (C):104475.
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  • Comparing cross-situational word learning, retention, and generalisation in children with autism and typical development.Calum Hartley, Laura-Ashleigh Bird & Padraic Monaghan - 2020 - Cognition 200 (C):104265.
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  • (1 other version)Canalization of Language Structure From Environmental Constraints: A Computational Model of Word Learning From Multiple Cues.Padraic Monaghan - 2017 - Topics in Cognitive Science 9 (1):21-34.
    There is substantial variation in language experience, yet there is surprising similarity in the language structure acquired. Constraints on language structure may be external modulators that result in this canalization of language structure, or else they may derive from the broader, communicative environment in which language is acquired. In this paper, the latter perspective is tested for its adequacy in explaining robustness of language learning to environmental variation. A computational model of word learning from cross-situational, multimodal information was constructed and (...)
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  • Simultaneous segmentation and generalisation of non-adjacent dependencies from continuous speech.Rebecca L. A. Frost & Padraic Monaghan - 2016 - Cognition 147 (C):70-74.
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  • A Single Paradigm for Implicit and Statistical Learning.Padraic Monaghan, Christine Schoetensack & Patrick Rebuschat - 2019 - Topics in Cognitive Science 11 (3):536-554.
    This article focuses on the implicit statistical learning of words and syntax. Monaghan, Schoetensack and Rebuschat introduce a novel paradigm that combines theoretical and methodological insights from the two research traditions, implicit learning and statistical learning. Their cross‐situational learning paradigm has been used in the statistical learning literature, while their measures of awareness have widely been used in implicit learning research. They illustrate how the two literatures can be conjoined in a single paradigm to explore implicit statistical learning.
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  • Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.Chi-Hsin Chen, Lisa Gershkoff-Stowe, Chih-Yi Wu, Hintat Cheung & Chen Yu - 2017 - Cognitive Science 41 (6):1485-1509.
    Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross‐situational learning paradigm to test whether English speakers were able to use co‐occurrences to learn word‐to‐object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership (...)
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  • Gavagai Is as Gavagai Does: Learning Nouns and Verbs From Cross‐Situational Statistics.Padraic Monaghan, Karen Mattock, Robert A. I. Davies & Alastair C. Smith - 2015 - Cognitive Science 39 (5):1099-1112.
    Learning to map words onto their referents is difficult, because there are multiple possibilities for forming these mappings. Cross-situational learning studies have shown that word-object mappings can be learned across multiple situations, as can verbs when presented in a syntactic context. However, these previous studies have presented either nouns or verbs in ambiguous contexts and thus bypass much of the complexity of multiple grammatical categories in speech. We show that noun word learning in adults is robust when objects are moving, (...)
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  • An amodal shared resource model of language-mediated visual attention.Alastair C. Smith, Padraic Monaghan & Falk Huettig - 2013 - Frontiers in Psychology 4.
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