Creating Large-Scale Multilingual Cognate Tables
Winston M.C. Wu, David Yarowsky · 2018
Low-resource languages often suffer from a lack of high-coverage lexical resources.In this paper, we propose a method to generate cognate tables by clustering words from existing lexical resources.We then employ character-based machine translation methods in solving the task of cognate chain completion by inducing missing word translations from lower-coverage dictionaries to fill gaps in the cognate chain, finding improvements over single language pair baselines when employing simple but novel multi-language system combination on the Romance and Turkic language families.For the Romance family, we show that system combination using the results of clustering outperforms weights derived from the historical-linguistic scholarship on language phylogenies.Our approach is applicable to any language family and has not been previously performed at such scale.The cognate tables are released to the research community.