9 found
  1.  18
    A Self‐Organizing Approach to Subject–Verb Number Agreement.Garrett Smith, Julie Franck & Whitney Tabor - 2018 - Cognitive Science 42 (S4):1043-1074.
    We present a self-organizing approach to sentence processing that sheds new light on notional plurality effects in agreement attraction, using pseudopartitive subject noun phrases. We first show that notional plurality ratings predict verb agreement choices in pseudopartitives, in line with the “Marking” component of the Marking and Morphing theory of agreement processing. However, no account to date has derived notional plurality values from independently needed principles of language processing. We argue on the basis of new experimental evidence and a dynamical (...)
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  2.  22
    Encoding and Retrieval Interference in Sentence Comprehension: Evidence From Agreement.Sandra Villata, Whitney Tabor & Julie Franck - 2018 - Frontiers in Psychology 9.
  3.  19
    Dynamical Models of Sentence Processing.Whitney Tabor & Michael K. Tanenhaus - 1999 - Cognitive Science 23 (4):491-515.
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  4.  50
    Impulse Processing: A Dynamical Systems Model of Incremental Eye Movements in the Visual World Paradigm.Anuenue Kukona & Whitney Tabor - 2011 - Cognitive Science 35 (6):1009-1051.
    The Visual World Paradigm (VWP) presents listeners with a challenging problem: They must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on a (...)
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  5.  78
    Fractal Analysis Illuminates the Form of Connectionist Structural Gradualness.Whitney Tabor, Pyeong Whan Cho & Emily Szkudlarek - 2013 - Topics in Cognitive Science 5 (3):634-667.
    We examine two connectionist networks—a fractal learning neural network (FLNN) and a Simple Recurrent Network (SRN)—that are trained to process center-embedded symbol sequences. Previous work provides evidence that connectionist networks trained on infinite-state languages tend to form fractal encodings. Most such work focuses on simple counting recursion cases (e.g., anbn), which are not comparable to the complex recursive patterns seen in natural language syntax. Here, we consider exponential state growth cases (including mirror recursion), describe a new training scheme that seems (...)
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  6.  52
    Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task.Whitney Tabor, Pyeong W. Cho & Harry Dankowicz - 2013 - Cognitive Science 37 (7):1193-1227.
    Human participants and recurrent (“connectionist”) neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular (“strong”) classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks’ encoding systems. We analyzed our network using dynamical systems theory, revealing topological and geometric properties that can (...)
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  7.  35
    Niall Griffith and Peter M. Todd, Eds., Musical Networks: Parallel Distributed Perception and Performance. [REVIEW]Whitney Tabor - 2001 - Minds and Machines 11 (4):597-602.
  8.  23
    Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language.Pyeong Whan Cho, Emily Szkudlarek & Whitney Tabor - 2016 - Frontiers in Psychology 7.
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  9.  1
    A Self-Organized Sentence Processing Theory of Gradience: The Case of Islands.Sandra Villata & Whitney Tabor - 2022 - Cognition 222:104943.
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