How Well Do Automatic Methods for Language Comparison Work?

There are more than 7,000 languages spoken worldwide. Many languages have evolved from a common ancestry line but we do not yet know where all the languages have come from and why there is such a great diversity. To find out how languages are related and form a family, linguists compare them by sifting through dictionaries, grammars or word lists. Recently, scholars have proposed automatic methods to compare languages more efficiently. However, many classical linguists do not trust these methods. JOHANN-MATTIS LIST wants to know how well these automatic methods for language comparison really perform. As he describes in this video, his research team compared the algorithms’ output directly with the judgment of experts using a data set covering more than five language families. They found that some algorithms perform remarkably well. This means that automatic methods of language comparison have reached a level of performance that allows linguists to use them as a pre-viewing tool.

DOI:

https://doi.org/10.21036/LTPUB10576

Max Planck Institute for Geoanthropology

The Max Planck Institute of Geoanthropology (MPI-GEA) focuses on the interrelationships between natural and human-made systems, looking into the deep past and distant future to examine how humanity has driven the emergence of the Anthropocene – the geological period in which human activities began significantly impacting our planet’s climate and ecosystems – and how we can still positively influence its course. The transdisciplinary research at MPI-GEA will bring together research areas represented by all three scientific sections of the MPG: Biology & Medicine; Chemistry, Physics and Technology; and Human Sciences. Corresponding inter- and transdisciplinary research projects concern, for example, planetary urbanisation, the global food system, and global material, energy and information flows.

Max Planck Institute for Geoanthropology

Original Publication

The Potential of Automatic Word Comparison for Historical Linguistics

Johann‐Mattis List

,

Simon J. Greenhill

,

Russell D. Gray

Published in 2017