Exposure and Emergence in Usage-Based Grammar

Dunn, J. (In Press). “Exposure and Emergence in Usage-Based Grammar: Computational Experiments in 35 Languages.” Cognitive Linguistics. Abstract. This paper uses computational experiments to explore the role of exposure in the emergence of construction grammars. While usage-based grammars are hypothesized to depend on a learner’s exposure to actual language use, the mechanisms of such exposure … More Exposure and Emergence in Usage-Based Grammar

Register Variation Remains Stable Across 60 Languages

Li, H.; Dunn, J.; and Nini, A. (In Press). “Register Variation Remains Stable Across 60 Languages.” Corpus Linguistics and Linguistic Theory. Abstract. This paper measures the stability of cross-linguistic register variation. A register is a variety of a language that is associated with extra-linguistic context. The relationship between a register and its context is functional: … More Register Variation Remains Stable Across 60 Languages

Stability of Syntactic Dialect Classification Over Space and Time

Dunn, J. and Wong, S. (2022). “Stability of Syntactic Dialect Classification Over Space and Time.” In Proceedings of International Conference on Computational Linguistics (COLING 2022). 26-36. Abstract. This paper analyses the degree to which dialect classifiers based on syntactic representations remain stable over space and time. While previous work has shown that the combination of … More Stability of Syntactic Dialect Classification Over Space and Time

Corpus similarity measures remain robust across diverse languages

Li, H. & Dunn, J. (2022). “Corpus similarity measures remain robust across diverse languages.” Lingua. Abstract. This paper experiments with frequency-based corpus similarity measures across 39 languages using a register prediction task. The goal is to quantify (i) the distance between different corpora from the same language and (ii) the homogeneity of individual corpora. Both … More Corpus similarity measures remain robust across diverse languages

Cognitive Linguistics Meets Computational Linguistics

Dunn, J. (2022). “Cognitive Linguistics Meets Computational Linguistics: Construction Grammar, Dialectology, and Linguistic Diversity.” In Tay, D. & Xie Pan, M. (eds.), Data Analytics in Cognitive Linguistics: Methods and Insights. 273-308. Berlin: De Gruyter. Abstract. Computational linguistics and cognitive linguistics come together when we use data-driven methods to conduct linguistic experiments on corpora. This chapter … More Cognitive Linguistics Meets Computational Linguistics

Language Identification for Austronesian Languages

Dunn, J. & Nijhof, W. (2022). “Language Identification for Austronesian Languages.” In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association. 6530‑6539 Abstract. This paper provides language identification models for low- and under-resourced languages in the Pacific region with a focus on previously unavailable Austronesian languages. Accurate … More Language Identification for Austronesian Languages

Predicting Embedding Reliability in Low-Resource Settings

Dunn, J.; Li, H.; & Sastre, D. (2022). “Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures.” In Proceedings of the 13th International Conference on Language Resources and Evaluation. European Language Resources Association. 6461-6470. Abstract This paper simulates a low-resource setting across 17 languages in order to evaluate embedding similarity, stability, and reliability under … More Predicting Embedding Reliability in Low-Resource Settings

Automatic Identification of Metaphoric Utterances

Dunn, J. (2013). Automatic Identification of Metaphoric Utterances. PhD Dissertation. Purdue University. Abstract. This dissertation analyzes the problem of metaphor identification in linguistic and computational semantics, considering both manual and automatic approaches. It describes a manual approach to metaphor identification, the Metaphoricity Measurement Procedure (MMP), and compares this approach with other manual approaches. The dissertation … More Automatic Identification of Metaphoric Utterances

Towards a Computational Model of Metaphor

Dunn, J. (2010). Towards a Computational Model of Metaphor. MA Thesis. Purdue University. Abstract. This thesis works towards a micro-theory of metaphor within the ontological semantics framework. It does so using a parameter-based system modeled roughly after Attardo and Raskin’s (1991) general theory of verbal humor. At the same time, it tries to convert Lakoff … More Towards a Computational Model of Metaphor

Construction Grammars Converge Given Increased Exposure

Dunn, J. & Tayyar Madabushi, H. (2021). “Learned Construction Grammars Converge Across RegistersGiven Increased Exposure.” Proceedings of the Conference on Computational Natural Language Learning (CoNLL 2021). Association for Computational Linguistics. Abstract. This paper measures the impact of increased exposure on whether learned construction grammars converge onto shared representations when trained on data from different registers. … More Construction Grammars Converge Given Increased Exposure