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  1.  25
    Domain Generality Versus Modality Specificity: The Paradox of Statistical Learning.Ram Frost, Blair C. Armstrong, Noam Siegelman & Morten H. Christiansen - 2015 - Trends in Cognitive Sciences 19 (3):117-125.
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  2.  31
    Towards a Universal Model of Reading.Ram Frost, Christina Behme, Madeleine El Beveridge, Thomas H. Bak, Jeffrey S. Bowers, Max Coltheart, Stephen Crain, Colin J. Davis, S. Hélène Deacon & Laurie Beth Feldman - 2012 - Behavioral and Brain Sciences 35 (5):263.
    In the last decade, reading research has seen a paradigmatic shift. A new wave of computational models of orthographic processing that offer various forms of noisy position or context-sensitive coding have revolutionized the field of visual word recognition. The influx of such models stems mainly from consistent findings, coming mostly from European languages, regarding an apparent insensitivity of skilled readers to letter order. Underlying the current revolution is the theoretical assumption that the insensitivity of readers to letter order reflects the (...)
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  3.  18
    The What, When, Where, and How of Visual Word Recognition.Manuel Carreiras, Blair C. Armstrong, Manuel Perea & Ram Frost - 2014 - Trends in Cognitive Sciences 18 (2):90-98.
  4.  13
    Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?Noam Siegelman, Louisa Bogaerts, Ofer Kronenfeld & Ram Frost - 2018 - Cognitive Science 42 (S3):692-727.
    From a theoretical perspective, most discussions of statistical learning have focused on the possible “statistical” properties that are the object of learning. Much less attention has been given to defining what “learning” is in the context of “statistical learning.” One major difficulty is that SL research has been monitoring participants’ performance in laboratory settings with a strikingly narrow set of tasks, where learning is typically assessed offline, through a set of two-alternative-forced-choice questions, which follow a brief visual or auditory familiarization (...)
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  5.  9
    Words with and Without Internal Structure: What Determines the Nature of Orthographic and Morphological Processing?Hadas Velan & Ram Frost - 2011 - Cognition 118 (2):141-156.
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  6.  29
    Towards a Universal Neurobiological Architecture for Learning to Read.Marcin Szwed, Fabien Vinckier, Laurent Cohen, Stanislas Dehaene & Ram Frost - 2012 - Behavioral and Brain Sciences 35 (5):308.
    Letter-position tolerance varies across languages. This observation suggests that the neural code for letter strings may also be subtly different. Although language-specific models remain useful, we should endeavor to develop a universal model of reading acquisition which incorporates crucial neurobiological constraints. Such a model, through a progressive internalization of phonological and lexical regularities, could perhaps converge onto the language-specific properties outlined by Frost.
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  7.  3
    Linguistic Entrenchment: Prior Knowledge Impacts Statistical Learning Performance.Noam Siegelman, Louisa Bogaerts, Amit Elazar, Joanne Arciuli & Ram Frost - 2018 - Cognition 177:198-213.
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  8.  3
    A Universal Approach to Modeling Visual Word Recognition and Reading: Not Only Possible, but Also Inevitable.Ram Frost - 2012 - Behavioral and Brain Sciences 35 (5):310-329.
    I have argued that orthographic processing cannot be understood and modeled without considering the manner in which orthographic structure represents phonological, semantic, and morphological information in a given writing system. A reading theory, therefore, must be a theory of the interaction of the reader with his/her linguistic environment. This outlines a novel approach to studying and modeling visual word recognition, an approach that focuses on the common cognitive principles involved in processing printed words across different writing systems. These claims were (...)
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  9.  32
    Linguistic Theory and Psychological Reality: A Reply to Boudelaa & Marslen-Wilson.Shlomo Bentin & Ram Frost - 2001 - Cognition 81 (1):113-118.
  10.  26
    Writing Systems: Not Optimal, but Good Enough.Mark S. Seidenberg & Ram Frost - 2012 - Behavioral and Brain Sciences 35 (5):305.
    Languages and writing systems result from satisfying multiple constraints related to learning, comprehension, production, and their biological bases. Orthographies are not optimal because these constraints often conflict, with further deviations due to accidents of history and geography. Things tend to even out because writing systems and the languages they represent exhibit systematic trade-offs between orthographic depth and morphological complexity.
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  11.  18
    What and Where is the Word?Catherine McBride-Chang, Hsuan-Chih Chen, Benjawan Kasisopa, Denis Burnham, Ronan Reilly, Paavo Leppänen & Ram Frost - 2012 - Behavioral and Brain Sciences 35 (5):295.
    Examples from Chinese, Thai, and Finnish illustrate why researchers cannot always be confident about the precise nature of the word unit. Understanding ambiguities regarding where a word begins and ends, and how to model word recognition when many derivations of a word are possible, is essential for universal theories of reading applied to both developing and expert readers.
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  12.  4
    Phonetic Recoding of Print and its Effect on the Detection of Concurrent Speech in Amplitude-Modulated Noise.Ram Frost - 1991 - Cognition 39 (3):195-214.
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