Determining Dutch dialect phylogeny using bayesian inference

Abstract

In this thesis, bayesian inference is used to determine the phylogeny of Dutch dialects. Bayesian inference is a computational method that can be used to calculate which phylogenetic tree has the highest probability, given the data. Dialect data from the Reeks Nederlandse Dialectatlassen, a corpus of words in several Dutch dialects, serves as input for the bayesian algorithm. The data was aligned and converted to phonological features. The trees generated by bayesian inference were evaluated by comparing them with an existing dialect map by Daan and Blok.