Johann-Mattis List How Well Do Automatic Methods for Language Comparison Work?
© Maximilian Dörrbecker
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Max Planck Institute for the Science of Human History
The Max Planck Institute for the Science of Human History conducts basic research using modern analytical methods with the aim of a multidisciplinary and integrated science of human history. It seeks to bridge the gap between historical disciplines and the natural sciences. Scientists from a range of fields, such as biology, linguistics, archaeology, anthropology and history jointly work on innovative methods, in particular in the fields of cutting-edge genetic and proteomic sequencing, bioinformatics, archaeological science, computational modeling, language databases, and phylogeography. This thoroughly integrated, interdisciplinary approach will address long-standing questions about human history – including some previously deemed difficult, or even completely intractable – as well as novel questions inspired by the new horizons that cutting edge methods open up. (Source)
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.
LT Video Publication DOI: https://doi.org/10.21036/LTPUB10576
The Potential of Automatic Word Comparison for Historical Linguistics
- Johann-Mattis List, Simon J. Greenhill and Russell D. Gray
- PloS one
- Published in 2017