A tentative model for dimensionless phoneme distance from binary distinctive features

TL;DR

This paper introduces a tentative model for calculating dimensionless phoneme distances based on binary features, useful for phoneme alignment and language phylogenetics, especially when empirical priors are unavailable.

Contribution

It presents a novel, linear-consistent model for phoneme distance measurement using binary features, applicable to sequence alignment and Bayesian language analysis.

Findings

Model shows linear consistency with binary features

Can be used for phoneme sequence alignment

Supports Bayesian phylogenetic analysis

Abstract

This work proposes a tentative model for the calculation of dimensionless distances between phonemes; sounds are described with binary distinctive features and distances show linear consistency in terms of such features. The model can be used as a scoring function for local and global pairwise alignment of phoneme sequences, and the distances can be used as prior probabilities for Bayesian analyses on the phylogenetic relationship between languages, particularly for cognate identification in cases where no empirical prior probability is available.