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Publication . Article . 2021

Automated identification of borrowings in multilingual wordlists

Johann-Mattis List; Robert Forkel;
Open Access
Abstract
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.
Subjects by Vocabulary

Microsoft Academic Graph classification: Artificial intelligence business.industry business Southern china Computer science Task (project management) Natural language processing computer.software_genre computer Identification (information) Historical linguistics Computational linguistics Language evolution

Subjects

computational linguistics, historical linguistics, lexical borrowing, borrowing detection, computational historical linguistics, Research Article, Articles

Related Organizations
Funded by
EC| CALC
Project
CALC
Computer-Assisted Language Comparison: Reconciling Computational and Classical Approaches in Historical Linguistics
  • Funder: European Commission (EC)
  • Project Code: 715618
  • Funding stream: H2020 | ERC | ERC-STG
Validated by funder
Related to Research communities
Digital Humanities and Cultural Heritage
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