The Potential of Automatic Word Comparison for Historical Linguistics.

ABSTRACT: The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words.

SUBMITTER: List JM 

PROVIDER: S-EPMC5271327 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature