Production vs Perception: The Role of Individuality in Usage-Based Grammar Induction

Dunn, J. & Nini, A. (2021). “Production vs Perception: The Role of Individuality in Usage-Based Grammar Induction.” Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (NAACL 2021). Association for Computational Linguistics. 149-159. Abstract. This paper asks whether a distinction between production-based and perception-based grammar induction influences either (i) the growth curve of grammars … More Production vs Perception: The Role of Individuality in Usage-Based Grammar Induction

Modeling Global Syntactic Variation in English

Dunn, J. (2019). “Modeling Global Syntactic Variation in English Using Dialect Classification.” In Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects (NAACL 19). Association for Computational Linguistics. 42-53. Abstract. This paper evaluates global-scale dialect identification for 14 national varieties of English as a means for studying syntactic variation. The paper … More Modeling Global Syntactic Variation in English

Frequency vs. Association in Usage-Based Grammar

Dunn, J. (2019). “Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar.” In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (NAACL 19). Association for Computational Linguistics. 117-128. Abstract. A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This … More Frequency vs. Association in Usage-Based Grammar

Computational Learning of Construction Grammars

Dunn, J. (2017). “Computational Learning of Construction Grammars.” Language and Cognition, 9(2): 254-292. Abstract. This paper presents an algorithm for learning the construction grammar of a language from a large corpus. This grammar induction algorithm has two goals: first, to show that construction grammars are learnable without highly specified innate structure; second, to develop a … More Computational Learning of Construction Grammars

Modeling the Complexity and Descriptive Adequacy of Construction Grammars

Dunn, J. (2018). “Modeling the Complexity and Descriptive Adequacy of Construction Grammars.” In Proceedings of the Society for Computation in Linguistics (SCiL 2018). Stroudsburg, PA: Association for Computational Linguistics. 81-90. Abstract. This paper uses the Minimum Description Length paradigm to model the complexity of CxGs (operationalized as the encoding size of a grammar) alongside their … More Modeling the Complexity and Descriptive Adequacy of Construction Grammars

Finding Variants for Construction-Based Dialectometry

Dunn, J. (2018). “Finding Variants for Construction-Based Dialectometry: A Corpus-Based Approach to Regional CxGs.” Cognitive Linguistics, 29(2): 275-311. Abstract. This paper develops a construction-based dialectometry capable of identifying previously unknown constructions and measuring the degree to which a given construction is subject to regional variation. The central idea is to learn a grammar of constructions … More Finding Variants for Construction-Based Dialectometry