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Academic Paper

Title: Distributions of Cognates in Europe as Based on Levenshtein Distance
Author: Job J. Schepens
Author: Ton Dijkstra
Institution: Radboud Universiteit Nijmegen
Author: Franc Grootjen
Institution: Radboud Universiteit Nijmegen
Linguistic Field: Computational Linguistics
Subject Language: Dutch
Abstract: Researchers on bilingual processing can benefit from computational tools developed in artificial intelligence. We show that a normalized Levenshtein distance function can efficiently and reliably simulate bilingual orthographic similarity ratings. Orthographic similarity distributions of cognates and non-cognates were identified across pairs of six European languages: English, German, French, Spanish, Italian, and Dutch. Semantic equivalence was determined using the conceptual structure of a translation database. By using a similarity threshold, large numbers of cognates could be selected that nearly completely included the stimulus materials of experimental studies. The identified numbers of form-similar and identical cognates correlated highly with branch lengths of phylogenetic language family trees, supporting the usefulness of the new measure for cross-language comparison. The normalized Levenshtein distance function can be considered as a new formal model of cross-language orthographic similarity.


This article appears IN Bilingualism: Language and Cognition Vol. 15, Issue 1, which you can READ on Cambridge's site or on LINGUIST .

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