A Corpus-based Study on Russian Translation of K-pop Lyrics and Its Naturalness
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This paper examines Russian translations of K-pop lyrics focusing on their patterns and errors. For this purpose, both qualitative and quantitative methods, including corpus analysis are used. Based on the manually revised Korean-Russian parallel corpus, the aligned texts are compared and analyzed at the morpho-syntactic and semantic levels. Considering existing song translation theories and translation strategies of cultural-specific items, this study takes the broadly accepted concepts of ‘prosodic match’ and ‘semantic-reflexive match’ proposed by Franzon(2008) as a framework for data analysis. The number of syllables, word correspondences, and sentence correspondences between the language pairs were discussed accordingly. To evaluate the syntactic naturalness, in particular, the Korean-Russian Parallel Corpus 2021 constructed by the National Institute of the Korean Language was used as a reference corpus to compare the number of words or syllables in the texts. The analysis of words, expressions, and alternations in sentences leads us to a better understanding of the patterns and strategies of Korean-Russian translation and types of translation errors in fan translation. Investigating how words or expressions that commonly appear in popular songs correspond to Russian can segue into constructing datasets, which contribute to the quality of not only human translation but also machine translation. The present study is also expected to contribute to building an accurate Korean-Russian parallel corpus or even an error-annotated corpus which would be helpful to second language learners in both countries.
Abstract
This paper examines Russian translations of K-pop lyrics focusing on their patterns and errors. For this purpose, both qualitative and quantitative methods, including corpus analysis are used. Based on the manually revised Korean-Russian parallel corpus, the aligned texts are compared and analyzed at the morpho-syntactic and semantic levels. Considering existing song translation theories and translation strategies of cultural-specific items, this study takes the broadly accepted concepts of ‘prosodic match’ and ‘semantic-reflexive match’ proposed by Franzon(2008) as a framework for data analysis. The number of syllables, word correspondences, and sentence correspondences between the language pairs were discussed accordingly. To evaluate the syntactic naturalness, in particular, the Korean-Russian Parallel Corpus 2021 constructed by the National Institute of the Korean Language was used as a reference corpus to compare the number of words or syllables in the texts. The analysis of words, expressions, and alternations in sentences leads us to a better understanding of the patterns and strategies of Korean-Russian translation and types of translation errors in fan translation. Investigating how words or expressions that commonly appear in popular songs correspond to Russian can segue into constructing datasets, which contribute to the quality of not only human translation but also machine translation. The present study is also expected to contribute to building an accurate Korean-Russian parallel corpus or even an error-annotated corpus which would be helpful to second language learners in both countries.
참고문헌 (15)
- (2022)[URL]
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