A Corpus-Based Comparative Study of Errors in Russian-Chinese Bidirectional Translation by Native Chinese Speakers

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Authors: Junling Gu, Jiayi Gao, Lei Liu, Wei Wang
Cited by: 0
References: 23

Abstract

This corpus-based study investigates translation error types in Russian-Chinese bidirectional translation by native Chinese speakers through quantitative analysis of 206 competition entries from the 16th Global Russian-Chinese Translation Competition. Addressing typological and translational gaps in Russian-Chinese and Chinese-Russian pairs, the study employs a tripartite error taxonomy (formal, semantic, and pragmatic aspects) to examine directional asymmetry in error distributions. These error distributions reveal significant directional effects (χ 2 tests, p < .001): Russian-to-Chinese translation direction exhibits more semantic errors (68.67% vs. 57.09%) due to decoding challenges in Russian’s synthetic features, while Chinese-to-Russian translation direction shows more formal errors (35.68% vs. 21.41%), reflecting morphological encoding challenges in Russian’s inflectional morphology due to L1 negative transfer. Based on these, the study concludes three findings. Firstly, typological differences between Russian inflectional morphology and Chinese analytic morphology can cause formal translation errors. Secondly, conceptual differences between western and eastern cultures can cause semantic translation errors. Thirdly, communicative and rhetorical differences can cause pragmatic translation errors. These findings demonstrate that semantic errors persist as the primary translation challenge across two directions. The study findings can contribute to translation studies by providing empirical evidence for directionality effects in Slavic-Sino language pairs and deepen theoretical understanding of translation directionality in language pairs with distinct and typological features.

Fields of Study & Subjects

Translation Studies and Practices Natural Language Processing Techniques Categorization perception and language

Publication details

Journal / source
SAGE Open
Volume
16
Issue
1
Publication date
1 January 2026
Language
EN