What phoneme networks tell us about the age of language families

Abstract

Age estimation of language families is an important task in historical linguistics. In our study we present an approach that utilizes information about the diversity across sound inventories of language families for the task of age estimation. Our approach involves three steps: (1) the construction of a phoneme network, which is a bipartite network structure that represents language families and its phoneme inventories in network-theoretic terms, (2) the reconstruction of such a real-world data network in form of a preferential attachment synthetic process, and (3) the detection of the optimal preferential attachment noise parameter, for which the synthetic network is the best approximation of the real-world data network. Our statistical analysis reveals that the optimal noise parameter appears to be a good predictor for the age of a language family.