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Typological Word Order Correlations with Logistic Brownian Motion

  • In this study we address the question to what extent syntactic word-order traits of different languages have evolved under correlation and whether such dependencies can be found universally across all languages or restricted to specific language families.To do so, we use logistic Brownian Motion under a Bayesian framework to model the trait evolution for 768 languages from 34 language families. We test for trait correlations both in single families and universally over all families. Separate models reveal no universal correlation patterns and Bayes Factor analysis of models over all covered families also strongly indicate lineage specific correlation patters instead of universal dependencies.

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Metadaten
Author:Kai Hartung, Gerhard Jäger, Sören Gröttrup, Munir GeorgesORCiD
Language:English
Document Type:Conference Paper
Conference:4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP, Seattle (WA, USA), 14.07.2022
Year of first Publication:2022
published in (English):Proceedings of the 4th Workshop on Computational Typology and Multilingual NLP (SIGTYP 2022)
Editor(s):Ekaterina Vylomova, Edoardo Ponti, Ryan Cotterell
Publisher:Association for Computational Linguistics
Place of publication:Stroudsburg
ISBN:978-1-955917-93-3
First Page:22
Last Page:26
Article Number:2022.sigtyp-1.3
Review:peer-review
Open Access:ja
Tag:Brownian Motion; Typology
URL:https://aclanthology.org/2022.sigtyp-1.3
Supplement:https://github.com/hartunka/typologicalwordordercorrelations
Faculties / Institutes / Organizations:Fakultät Informatik
AImotion Bavaria
Licence (German):License Logo Creative Commons BY 4.0
Release Date:2022/08/01