A Probabilistic Approach to Language Change

Part of Advances in Neural Information Processing Systems 20 (NIPS 2007)

Bibtex Metadata Paper


Alexandre Bouchard-côté, Percy S. Liang, Dan Klein, Thomas Griffiths


We present a probabilistic approach to language change in which word forms are represented by phoneme sequences that undergo stochastic edits along the branches of a phylogenetic tree. Our framework combines the advantages of the classical comparative method with the robustness of corpus-based probabilistic models. We use this framework to explore the consequences of two different schemes for defining probabilistic models of phonological change, evaluating these schemes using the reconstruction of ancient word forms in Romance languages. The result is an efficient inference procedure for automatically inferring ancient word forms from modern languages, which can be generalized to support inferences about linguistic phylogenies.