incom.py - A Toolbox for Calculating Linguistic Distances and Asymmetries between Related Languages

Marius Mosbach, Irina Stenger, Tania Avgustinova, Dietrich Klakow

Abstract
Languages may be differently distant from each other and their mutual intelligibility may be asymmetric. In this paper we introduce incom.py, a toolbox for calculating linguistic distances and asymmetries between related languages. incom.py allows linguist experts to quickly and easily perform statistical analyses and compare those with experimental results. We demonstrate the efficacy of incom.py in an incomprehension experiment on two Slavic languages: Bulgarian and Russian. Using incom.py we were able to validate three methods to measure linguistic distances and asymmetries: Levenshtein distance, word adaptation surprisal, and conditional entropy as predictors of success in a reading intercomprehension experiment.
Anthology ID:
R19-1094
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
810–818
Language:
URL:
https://aclanthology.org/R19-1094
DOI:
10.26615/978-954-452-056-4_094
Bibkey:
Cite (ACL):
Marius Mosbach, Irina Stenger, Tania Avgustinova, and Dietrich Klakow. 2019. incom.py - A Toolbox for Calculating Linguistic Distances and Asymmetries between Related Languages. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 810–818, Varna, Bulgaria. INCOMA Ltd..
Cite (Informal):
incom.py - A Toolbox for Calculating Linguistic Distances and Asymmetries between Related Languages (Mosbach et al., RANLP 2019)
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https://preview.aclanthology.org/nschneid-patch-1/R19-1094.pdf
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