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Martin: Language Processing
March 7, 2022 @ 11:00 am - 12:00 pm
Constraints on theories of language processing
Andrea Martin, Max Planck Institute for Psycholinguistics
Human language is an example of a formally-describable system that is both statistical and algebraic. As such, its computational properties are markedly different than in other perception-action systems: hierarchical relationships between sounds, words, phrases, and sentences, structure-dependence, and the unbounded ability to combine smaller units into larger ones. These and other formal properties have long made language difficult to account for from a biological systems perspective, and within models of cognition. I focus on this foundational puzzle – essentially “what does a system need to represent information that is both algebraic and statistical?” – and discuss the computational requirements, including the role of neural oscillations across time, for what I believe is necessary for a system to represent and process language. I build on examples from cognitive neuroimaging data and computational simulations, and outline a developing theory that integrates basic insights from linguistics and psycholinguistics with the currency of neural computation, which in turn demarcates the boundary conditions for biological and artificial systems in contact with human language.
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Department of Psychology, Funding provided by the Sharon M. Guten Endowment Fund.