An algorithm for identifying cognates between related languages

Authors:
Jacques B. M. Guy
Affiliations:
Australian National University, Canberra, Australia
Venue:
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Year:
1984

Citing 1
Cited 1

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Bayesian identification of cognates and correspondences

SigMorPhon '07 Proceedings of Ninth Meeting of the ACL Special Interest Group in Computational Morphology and Phonology

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Abstract

The algorithm takes as only input a list of words, preferably but not necessarily in phonemic transcription, in any two putatively related languages, and sorts it into decreasing order of probable cognation. The processing of a 250-item bilingual list takes about five seconds of CPU time on a DEC KL1091, and requires 56 pages of core memory. The algorithm is given no information whatsoever about the phonemic transcription used, and even though cognate identification is carried out on the basis of a context-free one-for-one matching of individual characters, its cognation decisions are bettered by a trained linguist using more information only in cases of wordlists sharing less than 40% cognates and involving complex, multiple sound correspondences.