Rules, Analogy and Social Factors codetermine past-tense formation patterns in English

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Conference Contributions - Other
Publisher's DOI/URI
Thesis discipline
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University of Canterbury. Global, Cultural and Language Studies
University of Canterbury. School of Language, Social and Political Sciences
University of Canterbury. Linguistics
University of Canterbury. New Zealand Institute of Language, Brain & Behaviour
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Volume Title
Racz, P.
Beckner, C.
Hay, J.B.
Pierrehumbert, J.B.

We investigate past-tense formation preferences for five irregular English verb classes. We gathered data on a large scale using a nonce probe study implemented on Amazon Mechanical Turk. We compare a Minimal Generalization Learner (which infers stochastic rules) with a Generalized Context Model (which evaluates new items via analogy with existing items) as models of participant choices. Overall, the GCM is a better predictor, but the the MGL provides some additional predictive power. Because variation across speakers is greater than variation across items, we also explore individual-level factors as predictors. Females exhibited significantly more categorical choices than males, a finding that can be related to results in sociolinguistics.

Racz, P., Beckner, C., Hay, J.B., Pierrehumbert, J.B. (2014) Rules, Analogy and Social Factors codetermine past-tense formation patterns in English. Baltimore, MD, USA: Joint Workshop between SIGMORPHON and SIGFSM, Association for Computational Linguistics (MORPHFSM2014), 27 Jun 2014.
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Fields of Research::47 - Language, communication and culture::4703 - Language studies::470307 - English language
Fields of Research::47 - Language, communication and culture::4704 - Linguistics::470409 - Linguistic structures (incl. phonology, morphology and syntax)