Measures of lexical distance between languages

The idea of measuring distance between languages seems to have its roots in the work of the French explorer Dumont D'Urville \cite{Urv}. He collected comparative words lists of various languages during his voyages aboard the Astrolabe from 1826 to 1829 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, 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. Recently another group of scholars \cite{Bak, Hol} proposed a refined of our definition including a second normalization. In this paper we compare the information content of our definition with the refined version in order to decide which of the two can be applied with greater success to resolve relationships among languages.

Lexical evolution rates by automated stability measure

Phylogenetic trees can be reconstructed from the matrix which contains the distances between all pairs of languages in a family. Recently, we proposed a new method which uses normalized Levenshtein distances among words with same meaning and averages on all the items of a given list. Decisions about the number of items in the input lists for language comparison have been debated since the beginning of glottochronology. The point is that words associated to some of the meanings have a rapid lexical evolution. Therefore, a large vocabulary comparison is only apparently more accurate then a smaller one since many of the words do not carry any useful information. In principle, one should find the optimal length of the input lists studying the stability of the different items. In this paper we tackle the problem with an automated methodology only based on our normalized Levenshtein distance. With this approach, the program of an automated reconstruction of languages relationships is completed.

Automated words stability and languages phylogeny

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.