Learnability in optimality theory /
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Author / Creator: | Tesar, Bruce. |
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Imprint: | Cambridge, Mass. : MIT Press, ©2000. ©2000 |
Description: | 1 online resource (vi, 140 pages) : illustrations |
Language: | English |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11113607 |
Other authors / contributors: | Smolensky, Paul, 1955- |
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ISBN: | 0585354677 9780585354675 9780262284790 0262284790 0262264889 9780262264884 0262201267 9780262201261 |
Notes: | Includes bibliographical references (pages 133-138) and index. English. Print version record. |
Summary: | Annotation Highlighting the close relationship between linguistic explanation and learnability, Bruce Tesar and Paul Smolensky examine the implications of Optimality Theory (OT) for language learnability. They show how the core principles of OT lead to the learning principle of constraint demotion, the basis for a family of algorithms that infer constraint rankings from linguistic forms. Of primary concern to the authors are the ambiguity of the data received by the learner and the resulting interdependence of the core grammar and the structural analysis of overt linguistic forms. The authors argue that iterative approaches to interdependencies, inspired by work in statistical learning theory, can be successfully adapted to address the interdependencies of language learning. Both OT and Constraint Demotion play critical roles in their adaptation. The authors support their findings both formally and through simulations. They also illustrate how their approach could be extended to other language learning issues, including subset relations and the learning of phonological underlying forms. |
Other form: | Print version: Tesar, Bruce. Learnability in optimality theory. Cambridge, Mass. : MIT Press, ©2000 0262201267 |
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