Cognate Identification using Machine Translation
Shervin Malmasi, Mark Dras · 2015
In this paper we describe an approach to automatic cognate identification in mono-lingual texts using machine translation. This system was used as our entry in the 2015 ALTA shared task, achieving an F1-score of 63 % on the test set. Our pro-posed approach takes an input text in a source language and uses statistical ma-chine translation to create a word-aligned parallel text in the target language. A ro-bust measure of string distance, the Jaro-Winkler distance in this case, is then ap-plied to the pairs of aligned words to de-tect potential cognates. Further extensions to improve the method are also discussed. 1