I last taught this course in Fall 2019.<\/p>\n
NOTE: the content of this course varies from instance to instance.<\/p>\n
This course will focus on “numeric variants” of Optimality Theory that have been used increasingly in recent phonological work. Topics will include:<\/p>\n
Harmonic Grammar (HG)
\nStochastic Optimality Theory (StOT)
\nMaximum Entropy constraint-based grammars (MaxEnt)<\/p>\n
The course will go over the definitions and basic functioning of these theories, as well as critically examine their properties, the linguistic and psycholinguistic phenomena that motivate them, and the relative strengths and weaknesses of each relative to traditional OT and to each other. Along the way, the course will cover selected background material as necessary.<\/p>\n
Expected work from the course participants will include reading, participation in class discussion, occasional small assignments, and a term paper (due near the end of the semester). The paper will be on some topic related to the main theme of the course; paper topics will be approved in advance by the instructor.<\/p>\n
Legendre, Geraldine, Antonella Sorace & Paul Smolensky. 2006. The Optimality Theory – Harmonic Grammar connection. In Paul Smolensky and Geraldine Legendre (eds.), The Harmonic Mind, 339-402. Cambridge, MA: MIT Press.<\/p>\n
Pater, Joe. 2016. Universal grammar with weighted constraints. In John J. McCarthy and Joe Pater (eds.), Harmonic Grammar and Harmonic Serialism, 1-46. Bristol, CT: Equinox Publishing.<\/p>\n
Boersma, Paul & Bruce Hayes. 2001. Empirical tests of the Gradual Learning Algorithm. Linguistic Inquiry 32(1). 45-86. https:\/\/www.jstor.org\/stable\/4179137.<\/p>\n
Goldwater, Sharon & Mark Johnson. 2003. Learning OT constraint rankings using a maximum entropy model. Proceedings of the Workshop on Variation within Optimality Theory, 113-122.<\/p>\n
Hayes, Bruce & Colin Wilson. 2008. A maximum entropy model of phonotactics and phonotactic learning. Linguistic Inquiry 39(3). 379-440. https:\/\/www.jstor.org\/stable\/40071443.<\/p>\n
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