Automatic Inference of Sound Correspondence Patterns across Multiple Languages

Automatic Inference of Sound Correspondence Patterns across Multiple Languages Johann-Mattis List Department of Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Jena Sound correspondence patterns play a crucial role for linguistic reconstruction. Linguists use them to prove language relationship, to reconstruct proto-forms, and for classical phylogenetic reconstruction based on shared innovations. Cognate words that fail to conform with expected patterns can further point to various kinds of exceptions in sound change, such as analogy or assimilation of frequent words. Here I present an automatic method for the inference of sound correspondence patterns across multiple languages based on a network approach. The core idea is to represent all columns in aligned cognate sets as nodes in a network with edges representing the degree of compatibility between the nodes. The task of inferring all compatible correspondence sets can then be handled as the well-known minimum clique cover problem in graph theory, which essentially seeks to split the graph into the smallest number of cliques in which each node is represented by exactly one clique. The resulting partitions represent all correspondence patterns that can be inferred for a given data set. By excluding those patterns that occur in only a few cognate sets, the core of regularly recurring sound correspondences can be inferred. Based on this idea, the article presents a method for automatic correspondence pattern recognition, which is implemented as part of a Python library which supplements the article. To illustrate the usefulness of the method, I present how the inferred patterns can be used to predict words that have not been observed before. 1. Introduction By comparing the languages of the world, we gain invaluable insights into human prehistory, predating the appearance of written records by thousands of years. The clas- sical methods for historical language comparison, a collection of different techniques summarized under the term comparative method (Meillet 1954; Weiss 2015), date back to the early 19th century and have since then been constantly refined and improved (see Ross and Durie 1996 for details on the practical workflow). Thanks to the comparative method, linguists have made groundbreaking insights into language change in general and into the history of many specific language families (Campbell and Poser 2008) and external evidence has often confirmed the validity of the findings (McMahon and Submission received: 4 April 2018; revised version received: 3 October 2018; accepted for publication: 21 November 2018. doi:10.1162/COLI_a_00344 © 2019 Association for Computational Linguistics Published under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license Computational Linguistics Volume 45, Number 1 McMahon 2005, pages 10–14). With increasing amounts of data, however, the methods, which are largely manually applied, reach their practical limits. As a result, scholars are now increasingly trying to automate different aspects of the classical comparative methods (Kondrak 2000; Proki´c, Wieling, and Nerbonne 2009; List 2014). One of the fundamental insights of early historical linguistic research was that— as a result of systemic changes in the sound system of languages—genetically related languages exhibit …

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