arne rubehn

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Hi! I am a computational linguist, currently pursuing my PhD at the Chair of Multilingual Computational Linguistics at the University of Passau. I focus on computer-assisted, data-driven methods for historical linguistics with the goal of advancing comparative historical linguistics by the means of intelligent algorithmic methods, alleviating researchers’ workload by processing large-scale data efficiently. I currently persue methods for modelling phonetic and semantic properties of basic vocabulary in an embedded space.

I have studied Computational Linguistics, General Linguistics, and Latin at the University of Tübingen. Within my MA thesis project I have trained a neural network that estimates global probabilities for arbitrary sound changes. Additionally, I have years of working experience as a software developer for EtInEn (Etymological Inference Engine), a software for historical linguists that is being developed at the Linguistic Department in Tübingen.

research interests

My research usually concerns the computational modelling of linguistic questions, especially within the domains of:

  • historical linguistics
  • phonetics and phonology
  • lexical semantics and word formation
  • typology

Instead of focusing on individual languages or families, I aim at developing “generalist” models and methods in the light of large-scale, cross-linguistic applications.

news

Jun 07, 2025 Three accepted papers: Very happy to announce that our paper “Partial Colexifications Improve Concept Embeddings” (with Johann-Mattis List) has been accepted for the main conference of the Association of Computational Linguistics. Two more papers that I have co-authored were accepted to SIGTYP.
Jun 06, 2025 Talk held: The Potential of Partial Colexifications for Comparative Linguistics (with Johann-Mattis List). C-LESTE Workshop, University of Frankfurt, Germany.
May 09, 2025 Talk held: Improving Digitization Efforts in Comparative Linguistics. Workshop “Linguistic data and language comparison in light of the quantitative turn and big data”, University of Bern, Switzerland.