Non-Parametric Bayesian Areal Linguistics

TL;DR

This paper introduces a non-parametric Bayesian model for linguistic areal and phylogenetic analysis, improving language classification and feature hierarchy identification using advanced probabilistic methods.

Contribution

It presents a novel Bayesian framework combining Pitman-Yor process and Kingman's coalescent for modeling linguistic areas and phylogeny, enhancing language reconstruction.

Findings

Accurately recovers known linguistic areas

Identifies plausible hierarchy of areal features

Improves genetic reconstruction of languages

Abstract

We describe a statistical model over linguistic areas and phylogeny. Our model recovers known areas and identifies a plausible hierarchy of areal features. The use of areas improves genetic reconstruction of languages both qualitatively and quantitatively according to a variety of metrics. We model linguistic areas by a Pitman-Yor process and linguistic phylogeny by Kingman's coalescent.