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  1. Notational Variants and Cognition: The Case of Dependency Grammar.Ryan M. Nefdt & Giosué Baggio - forthcoming - Erkenntnis:1-31.
    In recent years, dependency grammars have established themselves as valuable tools in theoretical and computational linguistics. To many linguists, dependency grammars and the more standard constituency-based formalisms are notational variants. We argue that, beyond considerations of formal equivalence, cognition may also serve as a background for a genuine comparison between these different views of syntax. In this paper, we review and evaluate some of the most common arguments and evidence employed to advocate for the cognitive or neural reality of dependency (...)
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  • Learning the unlearnable: the role of missing evidence.Terry Regier & Susanne Gahl - 2004 - Cognition 93 (2):147-155.
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  • A Probabilistic Model of Melody Perception.David Temperley - 2008 - Cognitive Science 32 (2):418-444.
    This study presents a probabilistic model of melody perception, which infers the key of a melody and also judges the probability of the melody itself. The model uses Bayesian reasoning: For any “surface” pattern and underlying “structure,” we can infer the structure maximizing P(structure|surface) based on knowledge of P(surface, structure). The probability of the surface can then be calculated as ∑ P(surface, structure), summed over all structures. In this case, the surface is a pattern of notes; the structure is a (...)
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  • The learnability of abstract syntactic principles.Amy Perfors, Joshua B. Tenenbaum & Terry Regier - 2011 - Cognition 118 (3):306-338.
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  • What a Rational Parser Would Do.John T. Hale - 2011 - Cognitive Science 35 (3):399-443.
    This article examines cognitive process models of human sentence comprehension based on the idea of informed search. These models are rational in the sense that they strive to find a good syntactic analysis quickly. Informed search derives a new account of garden pathing that handles traditional counterexamples. It supports a symbolic explanation for local coherence as well as an algorithmic account of entropy reduction. The models are expressed in a broad framework for theories of human sentence comprehension.
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