Automated identification of borrowings in multilingual wordlists.
borrowing detection
computational historical linguistics
computational linguistics
historical linguistics
lexical borrowing
Journal
Open research Europe
ISSN: 2732-5121
Titre abrégé: Open Res Eur
Pays: Belgium
ID NLM: 9918230081006676
Informations de publication
Date de publication:
2021
2021
Historique:
accepted:
03
09
2021
medline:
23
3
2022
pubmed:
23
3
2022
entrez:
30
8
2023
Statut:
epublish
Résumé
Although lexical borrowing is an important aspect of language evolution, there have been few attempts to automate the identification of borrowings in lexical datasets. Moreover, none of the solutions which have been proposed so far identify borrowings across multiple languages. This study proposes a new method for the task and tests it on a newly compiled large comparative dataset of 48 South-East Asian languages from Southern China. The method yields very promising results, while it is conceptually straightforward and easy to apply. This makes the approach a perfect candidate for computer-assisted exploratory studies on lexical borrowing in contact areas.
Identifiants
pubmed: 37645101
doi: 10.12688/openreseurope.13843.3
pmc: PMC10445856
doi:
Types de publication
Journal Article
Langues
eng
Pagination
79Informations de copyright
Copyright: © 2022 List JM and Forkel R.
Déclaration de conflit d'intérêts
No competing interests were disclosed.
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