Using Cross-Lingual Part of Speech Tagging for Partially Reconstructing the Classic Language Family Tree Model

Anat Samohi, Daniel Weisberg Mitelman, Kfir Bar


Abstract
The tree model is well known for expressing the historic evolution of languages. This model has been considered as a method of describing genetic relationships between languages. Nevertheless, some researchers question the model’s ability to predict the proximity between two languages, since it represents genetic relatedness rather than linguistic resemblance. Defining other language proximity models has been an active research area for many years. In this paper we explore a part-of-speech model for defining proximity between languages using a multilingual language model that was fine-tuned on the task of cross-lingual part-of-speech tagging. We train the model on one language and evaluate it on another; the measured performance is then used to define the proximity between the two languages. By further developing the model, we show that it can reconstruct some parts of the tree model.
Anthology ID:
2022.lchange-1.8
Volume:
Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Nina Tahmasebi, Syrielle Montariol, Andrey Kutuzov, Simon Hengchen, Haim Dubossarsky, Lars Borin
Venue:
LChange
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
78–88
Language:
URL:
https://aclanthology.org/2022.lchange-1.8
DOI:
10.18653/v1/2022.lchange-1.8
Bibkey:
Cite (ACL):
Anat Samohi, Daniel Weisberg Mitelman, and Kfir Bar. 2022. Using Cross-Lingual Part of Speech Tagging for Partially Reconstructing the Classic Language Family Tree Model. In Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, pages 78–88, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Using Cross-Lingual Part of Speech Tagging for Partially Reconstructing the Classic Language Family Tree Model (Samohi et al., LChange 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lchange-1.8.pdf
Video:
 https://aclanthology.org/2022.lchange-1.8.mp4