Automated words stability and languages phylogeny

TL;DR

This paper introduces an automated method using normalized Levenshtein distance to measure language distances and analyze word stability and phylogeny, improving understanding of linguistic evolution and relationships.

Contribution

It presents a novel automated approach for assessing language relationships and word stability based solely on normalized Levenshtein distance, advancing computational historical linguistics.

Findings

The method effectively quantifies language distances.

Word stability varies with meaning and usage frequency.

Automated analysis aligns with traditional linguistic classifications.

Abstract

The idea of measuring distance between languages seems to have its roots in the work of the French explorer Dumont D'Urville (D'Urville 1832). He collected comparative words lists of various languages during his voyages aboard the Astrolabe from 1826 to1829 and, in his work about the geographical division of the Pacific, he proposed a method to measure the degree of relation among languages. The method used by modern glottochronology, developed by Morris Swadesh in the 1950s (Swadesh 1952), measures distances from the percentage of shared cognates, which are words with a common historical origin. Recently, we proposed a new automated method which uses normalized Levenshtein distance among words with the same meaning and averages on the words contained in a list. Another classical problem in glottochronology is the study of the stability of words corresponding to different meanings. Words, in fact, evolve because of lexical changes, borrowings and replacement at a rate which is not the same for all of them. The speed of lexical evolution is different for different meanings and it is probably related to the frequency of use of the associated words (Pagel et al. 2007). This problem is tackled here by an automated methodology only based on normalized Levenshtein distance.