A probabilistic approach to language change

Alexandre Bouchard-Côté, Percy Liang, Thomas L. Griffiths, Dan Klein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

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. This 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 by reconstructing ancient word forms of 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.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference
StatePublished - Dec 1 2009
Externally publishedYes
Event21st Annual Conference on Neural Information Processing Systems, NIPS 2007 - Vancouver, BC, Canada
Duration: Dec 3 2007Dec 6 2007

Publication series

NameAdvances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference

Other

Other21st Annual Conference on Neural Information Processing Systems, NIPS 2007
CountryCanada
CityVancouver, BC
Period12/3/0712/6/07

All Science Journal Classification (ASJC) codes

  • Information Systems

Fingerprint Dive into the research topics of 'A probabilistic approach to language change'. Together they form a unique fingerprint.

  • Cite this

    Bouchard-Côté, A., Liang, P., Griffiths, T. L., & Klein, D. (2009). A probabilistic approach to language change. In Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference (Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference).