Phonological distances for linguistic typology and the origin of Indo-European languages

TL;DR

This paper demonstrates that phoneme sequence analysis using information theory can effectively quantify linguistic relatedness, recover language families, and support hypotheses about Indo-European origins.

Contribution

It introduces a novel phonological distance metric based on phoneme dependencies that captures large-scale linguistic relationships and geographic origins.

Findings

Phoneme dependencies encode large-scale linguistic relatedness.

The phonological distance matrix recovers major language families.

A correlation with geographic distance supports the Steppe hypothesis.

Abstract

We show that short-range phoneme dependencies encode large-scale patterns of linguistic relatedness, with direct implications for quantitative typology and evolutionary linguistics. Specifically, using an information-theoretic framework, we argue that phoneme sequences modeled as second-order Markov chains essentially capture the statistical correlations of a phonological system. This finding enables us to quantify distances among 67 modern languages from a multilingual parallel corpus employing a distance metric that incorporates articulatory features of phonemes. The resulting phonological distance matrix recovers major language families and reveals signatures of contact-induced convergence. Remarkably, we obtain a clear correlation with geographic distance, allowing us to constrain a plausible homeland region for the Indo-European family, consistent with the Steppe hypothesis.