Predictability of Microsyntactic Units across Slavic Languages: A translation-based Study Inproceedings
Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), University of Tartu Library, Tallinn, Estonia, 2025.The paper presents the results of a free translation experiment, which was set up to explore Slavic cross-language intelligibility. In the experiment, native speakers of Russian were asked to read a sentence in one of the five Slavic languages and return a Russian translation of a highlighted item. The experiment is focused on microsyntactic units because they offer an increased intercomprehension difficulty due to opaque semantics. Each language is represented by at least 50 stimuli, and each stimulus has generated at least 20 responses. The levels of intercomprehension are captured by categorising participants‘ responses into seven types of translation solutions (paraphrase, correct, fluent_literal, awkward_literal, fantasy, noise, and empty), generally reflecting the level of the cross-linguistic intelligibility of the stimuli. The study aims to reveal linguistic factors that favour intercomprehension across Slavic languages. We use regression and correlation analysis to identify the most important intercomprehension predictors and statistical analysis to bring up the most typical cases and outliers. We explore several feature types that reflect the properties of the translation tasks and their outcomes, including point-wise phonological and orthographic distances, cosine similarities, surprisals, translation quality scores and translation solution entropy indices. The experimental data confirms the expected gradual increase of intelligibility from West-Slavic to East-Slavic languages for the speakers of Russian. We show that intelligibility is highly contingent on the ability of speakers to recognise and interpret formal similarities between languages as well as on the size of these similarities. For several Slavic languages, the context sentence complexity was a significant predictor of intelligibility.
@inproceedings{Kunilovskaya-etal-2025,
title = {Predictability of Microsyntactic Units across Slavic Languages: A translation-based Study},
author = {Maria Kunilovskaya and Iuliia Zaitova and Wei Xue and Irina Stenger and Tania Avgustinova},
url = {https://dspace.ut.ee/items/26e26504-9379-42cf-8f85-361a04dcd114},
year = {2025},
date = {2025},
booktitle = {Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)},
publisher = {University of Tartu Library},
address = {Tallinn, Estonia},
abstract = {
The paper presents the results of a free translation experiment, which was set up to explore Slavic cross-language intelligibility. In the experiment, native speakers of Russian were asked to read a sentence in one of the five Slavic languages and return a Russian translation of a highlighted item. The experiment is focused on microsyntactic units because they offer an increased intercomprehension difficulty due to opaque semantics. Each language is represented by at least 50 stimuli, and each stimulus has generated at least 20 responses. The levels of intercomprehension are captured by categorising participants' responses into seven types of translation solutions (paraphrase, correct, fluent_literal, awkward_literal, fantasy, noise, and empty), generally reflecting the level of the cross-linguistic intelligibility of the stimuli. The study aims to reveal linguistic factors that favour intercomprehension across Slavic languages. We use regression and correlation analysis to identify the most important intercomprehension predictors and statistical analysis to bring up the most typical cases and outliers. We explore several feature types that reflect the properties of the translation tasks and their outcomes, including point-wise phonological and orthographic distances, cosine similarities, surprisals, translation quality scores and translation solution entropy indices. The experimental data confirms the expected gradual increase of intelligibility from West-Slavic to East-Slavic languages for the speakers of Russian. We show that intelligibility is highly contingent on the ability of speakers to recognise and interpret formal similarities between languages as well as on the size of these similarities. For several Slavic languages, the context sentence complexity was a significant predictor of intelligibility.
pubstate = {published},
type = {inproceedings}
}