The Mathematical Assessment of Long‐Range Linguistic Relationships

Abstract

Language classification differs from biological cladistics in that monogenesis cannot be assumed. Before a cladogram or family tree can be accepted, linguists must be convinced that the languages are related at all. Morpheme tables, or word lists, provide a good framework for investigating relatedness, but methodologies for quantifying and assessing the data statistically are still being developed. The comparative method furnished a viable statistic, recurrent sound correspondences, but by no means to see whether they exceeded levels expected by chance. Organizing correspondences into contingency tables permitted hypothesis testing, with Monte Carlo resampling methods providing the flexibility to support a wide variety of test statistics, including different ways of computing sound recurrences and phonetic similarity. Thus, techniques from both the comparative method and multilateral comparison can be deployed with rigorous numeric assessment. Experiments seek to increase the power of the tests to explore new hypotheses and verify long-range language relationships. Brett Kessler

Comparative Reconstruction Probabilistically: The Role of Inventory and Phonotactics

“…This hypothesis assumes an understanding of what could have been produced by chance. It is somewhat common practice in computational historical linguistics to estimate the extent of random possibilities in a wordlist by simply permuting the words in that list in what is known as a Monte-Carlo simulation (Baxter, 1995;Kessler & Lehtonen, 2006;Croft, 2008;Kessler, 2008;Kessler, 2015;Hruschka et al, 2015;Zhang & Gong, 2016). Such an approach is reasonable because, by definition, each phonological word in a wordlist is permissible in that language, and, through Saussarian arbitrariness (1916), phonology and semantics cooccur freely.…”