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date: 13 November 2018

Summary and Keywords

Different methods exist for classifying languages, depending on whether the task is to work out the relations among languages already known to be related—internal language classification—or whether the task is to establish that certain languages are related—external language classification.

The comparative method in historical linguistics, developed during the latter part of the 19th century, represents one method for internal language classification; lexicostatistics, developed during the 1950s, represents another. Elements of lexicostatistics have been transformed and carried over into modern computational linguistic phylogenetics, and currently efforts are also being made to automate the comparative method. Recent years have seen rapid progress in the development of methods, tools, and resources for language classification. For instance, computational phylogenetic algorithms and software have made it possible to handle the classification of many languages using explicit models of language change, and data have been gathered for two thirds of the world’s language, allowing for rapid, exploratory classifications. There are also many open questions and venues for future research, for instance: What are the real-world counterparts to the nodes in a family tree structure? How can shortcomings in the traditional method of comparative historical linguistics be overcome? How can the understanding of the results that computational linguistic phylogenetics have to offer be improved?

External language classification, a notoriously difficult task, has also benefitted from the advent of computational power. While, in the past, the simultaneous comparison of many languages for the purpose of discovering deep genealogical links was carried out in a haphazard fashion, leaving too much room for the effect of chance similarities to kick in, this sort of activity can now be done in a systematic, objective way on an unprecedented scale. The ways of producing final, convincing evidence for a deep genealogical relation, however, have not changed much. There is some room for improvement in this area, but even more room for improvement in the way that proposals for long-distance relations are evaluated.

Keywords: comparative method, regular sound change, reconstruction, post hoc shared innovation, lexicostatistics, computational linguistic phylogenetics, mass comparison, ASJP, distance-based, character-based, Oswalt’s shift test

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