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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 Finding Variants for Construction-Based Dialectometry: A Corpus-Based Approach to Regional CxGs ... Dunn, Jonathan. - : arXiv, 2021 BASE Show details 2 Representations of Language Varieties Are Reliable Given Corpus Similarity Measures ... Dunn, Jonathan. - : arXiv, 2021 BASE Show details 3 Measuring Linguistic Diversity During COVID-19 ... Dunn, Jonathan; Coupe, Tom; Adams, Benjamin. - : arXiv, 2021 BASE Show details 4 Learned Construction Grammars Converge Across Registers Given Increased Exposure ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dunn, Jonathan; Tayyar Madabushi, Harish. - : Underline Science Inc., 2021 BASE Show details 5 Production vs Perception: The Role of Individuality in Usage-Based Grammar Induction ... Dunn, Jonathan; Nini, Andrea. - : arXiv, 2021 BASE Show details 6 Global Syntactic Variation in Seven Languages: Towards a Computational Dialectology ... Dunn, Jonathan. - : arXiv, 2021 Abstract: The goal of this paper is to provide a complete representation of regional linguistic variation on a global scale. To this end, the paper focuses on removing three constraints that have previously limited work within dialectology/dialectometry. First, rather than assuming a fixed and incomplete set of variants, we use Computational Construction Grammar to provide a replicable and falsifiable set of syntactic features. Second, rather than assuming a specific area of interest, we use global language mapping based on web-crawled and social media datasets to determine the selection of national varieties. Third, rather than looking at a single language in isolation, we model seven major languages together using the same methods: Arabic, English, French, German, Portuguese, Russian, and Spanish. Results show that models for each language are able to robustly predict the region-of-origin of held-out samples better using Construction Grammars than using simpler syntactic features. These global-scale experiments are ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2104.01306 https://dx.doi.org/10.48550/arxiv.2104.01306 BASE Hide details 7 Natural Language Processing for Corpus Linguistics ... Dunn, Jonathan. - : Code Ocean, 2021 BASE Show details 8 Learned Construction Grammars Converge Across Registers Given Increased Exposure Dunn, Jonathan; Tayyar Madabushi H. - : Association for Computational Linguistics, 2021 BASE Show details 9 Production vs Perception: The Role of Individuality in Usage-Based Grammar Induction Nini A; Dunn, Jonathan. - : Association for Computational Linguistics, 2021 BASE Show details 10 Representations of Language Varieties Are Reliable Given Corpus Similarity Measures Dunn, Jonathan. - : Association for Computational Linguistics, 2021 BASE Show details

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