Colin Wilson


2022

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Learning Input Strictly Local Functions: Comparing Approaches with Catalan Adjectives
Alex Shilen | Colin Wilson
Proceedings of the Society for Computation in Linguistics 2022

2021

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Learning the surface structure of wh-questions in English and French with a non-parametric Bayesian model
An Nguyen | Colin Wilson
Proceedings of the Society for Computation in Linguistics 2021

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Deep neural networks easily learn unnatural infixation and reduplication patterns
Coleman Haley | Colin Wilson
Proceedings of the Society for Computation in Linguistics 2021

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Were We There Already? Applying Minimal Generalization to the SIGMORPHON-UniMorph Shared Task on Cognitively Plausible Morphological Inflection
Colin Wilson | Jane S.Y. Li
Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology

Morphological rules with various levels of specificity can be learned from example lexemes by recursive application of minimal generalization (Albright and Hayes, 2002, 2003). A model that learns rules solely through minimal generalization was used to predict average human wug-test ratings from German, English, and Dutch in the SIGMORPHON-UniMorph 2021 Shared Task, with competitive results. Some formal properties of the minimal generalization operation were proved. An automatic method was developed to create wug-test stimuli for future experiments that investigate whether the model’s morphological generalizations are too minimal.

2020

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Extending adaptor grammars to learn phonological alternations
Canaan Breiss | Colin Wilson
Proceedings of the Society for Computation in Linguistics 2020