A Bayesian phylogenetic model with horizontal transfer for language evolution

Abstract:

Natural languages, as spoken nowadays, changed and evolved over time. Studying this evolutionary process using spatio-temporal models can give insights about migrations of the speakers in space and about the process of language change itself. Recently, Bayesian phylogeographic approaches have been adapted to linguistics and applied to case studies on different language families. However, some of their findings are highly debated and the lack of historical data makes it hard to validate these models.

In my dissertation project I develop a tool for spatio-temporal simulations of language evolution. Using these simulations we can demonstrate scenarios in which phylogeographic models fail to recover the true history behind the data. We apply this approach to evaluate two hypotheses: 1. "Phylogeographic methods fail to recover drift in human migrations" and 2. "Phylogenetic methods fail to recover the true relationship between languages under significant levels of borrowing". The latter example will be addressed again in a later stage of my PhD, where I want to extend current phylogeographic methods to account for borrowing.

About the Speaker

Nico Neureiter is a PhD student in Geographic Information Science at the URPP Language and Space Lab, University of Zurich. His research topic is the spatio-temporal modelling of language change.

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