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Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes
Inspired by work in comparative sociolinguistics and quantitative dialectometry, we sketch a corpus-based method (Variation-Based Distance & Similarity Modeling—VADIS for short) to rigorously quantify the similarity between varieties and dialects as a function of the correspondence of the ways i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861267/ https://www.ncbi.nlm.nih.gov/pubmed/33733112 http://dx.doi.org/10.3389/frai.2019.00023 |
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author | Szmrecsanyi, Benedikt Grafmiller, Jason Rosseel, Laura |
author_facet | Szmrecsanyi, Benedikt Grafmiller, Jason Rosseel, Laura |
author_sort | Szmrecsanyi, Benedikt |
collection | PubMed |
description | Inspired by work in comparative sociolinguistics and quantitative dialectometry, we sketch a corpus-based method (Variation-Based Distance & Similarity Modeling—VADIS for short) to rigorously quantify the similarity between varieties and dialects as a function of the correspondence of the ways in which language users choose between different ways of saying the same thing. To showcase the potential of the method, we present a case study that investigates three syntactic alternations in some nine international varieties of English. Key findings include that (a) probabilistic grammars are remarkably similar and stable across the varieties under study; (b) in many cases we see a cluster of “native” (a.k.a. Inner Circle) varieties, such as British English, whereas “non-native” (a.k.a. Outer Circle) varieties, such as Indian English, are a more heterogeneous group; and (c) coherence across alternations is less than perfect. |
format | Online Article Text |
id | pubmed-7861267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78612672021-03-16 Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes Szmrecsanyi, Benedikt Grafmiller, Jason Rosseel, Laura Front Artif Intell Artificial Intelligence Inspired by work in comparative sociolinguistics and quantitative dialectometry, we sketch a corpus-based method (Variation-Based Distance & Similarity Modeling—VADIS for short) to rigorously quantify the similarity between varieties and dialects as a function of the correspondence of the ways in which language users choose between different ways of saying the same thing. To showcase the potential of the method, we present a case study that investigates three syntactic alternations in some nine international varieties of English. Key findings include that (a) probabilistic grammars are remarkably similar and stable across the varieties under study; (b) in many cases we see a cluster of “native” (a.k.a. Inner Circle) varieties, such as British English, whereas “non-native” (a.k.a. Outer Circle) varieties, such as Indian English, are a more heterogeneous group; and (c) coherence across alternations is less than perfect. Frontiers Media S.A. 2019-11-05 /pmc/articles/PMC7861267/ /pubmed/33733112 http://dx.doi.org/10.3389/frai.2019.00023 Text en Copyright © 2019 Szmrecsanyi, Grafmiller and Rosseel. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Szmrecsanyi, Benedikt Grafmiller, Jason Rosseel, Laura Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes |
title | Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes |
title_full | Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes |
title_fullStr | Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes |
title_full_unstemmed | Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes |
title_short | Variation-Based Distance and Similarity Modeling: A Case Study in World Englishes |
title_sort | variation-based distance and similarity modeling: a case study in world englishes |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861267/ https://www.ncbi.nlm.nih.gov/pubmed/33733112 http://dx.doi.org/10.3389/frai.2019.00023 |
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