Think! Evidence

Memory and locality in natural language

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dc.contributor Edward Gibson and Roger Levy.
dc.contributor Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences.
dc.contributor Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences.
dc.creator Futrell, Richard Landy Jones
dc.date 2018-03-12T19:28:49Z
dc.date 2018-03-12T19:28:49Z
dc.date 2017
dc.date 2017
dc.date.accessioned 2019-05-10T17:25:41Z
dc.date.available 2019-05-10T17:25:41Z
dc.identifier http://hdl.handle.net/1721.1/114075
dc.identifier 1027213306
dc.identifier.uri https://evidence.thinkportal.org/handle/1721.1/114075
dc.description Thesis: Ph. D. in Cognitive Science, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2017.
dc.description Cataloged from PDF version of thesis.
dc.description Includes bibliographical references (pages 189-211).
dc.description I explore the hypothesis that the universal properties of human languages can be explained in terms of efficient communication given fixed human information processing constraints. I argue that under short-term memory constraints, optimal languages should exhibit information locality: words that depend on each other, both in their interpretation and in their statistical distribution, should be close to each other in linear order. The informationtheoretic approach to natural language motivates a study of quantitative syntax in Chapter 2, focusing on word order flexibility. In Chapter 3, I show comprehensive corpus evidence from over 40 languages that word order in grammar and usage is shaped by working memory constraints in the form of dependency locality: a pressure for syntactically linked words to be close. In Chapter 4, I develop a new formal model of language processing cost, called noisy-context surprisal, based on rational inference over noisy memory representations. This model unifies surprisal and memory effects and derives dependency locality effects as a subset of information locality effects. I show that the new processing model also resolves a long-standing paradox in the psycholinguistic literature, structural forgetting, where the effects of memory appear to be language-dependent. In the conclusion I discuss connections to probabilistic grammars, endocentricity, duality of patterning, incremental planning, and deep reinforcement learning.
dc.description by Richard Landy Jones Futrell.
dc.description Ph. D. in Cognitive Science
dc.format 211 pages
dc.format application/pdf
dc.language eng
dc.publisher Massachusetts Institute of Technology
dc.rights MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
dc.rights http://dspace.mit.edu/handle/1721.1/7582
dc.subject Brain and Cognitive Sciences.
dc.title Memory and locality in natural language
dc.type Thesis


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