Automated Rhythmic Device Search in Literary Texts Applied to Comparing Original and Translated Texts as Exemplified by English to Russian Translations

被引:0
作者
Lagutina, N. S. [1 ]
Lagutina, K. V. [1 ]
Boychuk, E. I. [2 ]
Vorontsova, I. A. [2 ]
Paramonov, I. V. [1 ]
机构
[1] Demidov Yaroslavl State Univ, Yaroslavl 150003, Russia
[2] Ushinsky Yaroslavl State Pedag Univ, Yaroslavl 150000, Russia
基金
俄罗斯基础研究基金会;
关键词
prose rhythm; rhythm analysis; natural language processing; rhythmic devices; automation;
D O I
10.3103/S0146411620070147
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Analysis of a translated text's functional equivalence to its original based on the attainment of rhythmic equivalence is an extremely important task of modern linguistics. The rhythmic component is an integral part of functional equivalence, which cannot be attained without reproducing the rhythmic devices of the original text. For the purposes of analyzing rhythmic devices in an original literary text and its translations, the authors have developed the software tool ProseRhythmDetector, which can find and visualize lexical and syntactic devices in English- and Russian-language prose, specifically anaphora, epiphora, symploce, anadiplosis, epanalepsis, reduplication, epistrophe, polysyndeton, and aposiopesis. The objective of this study is to present the results of the testing of ProseRhythmDetector on two English-language literary texts and their Russian translations: "Villette" by Charlotte Bronte and "The Black Prince" by Iris Murdoch. Using the results obtained by the software tool, the authors cross-referenced rhythmic devices in the original and translated texts and compared rhythm aspects and their contexts. The experiment made it possible to identify specific characteristics of a translator's rendition of the author's style, as well as detect and explain cases in which the use of rhythmic devices in the translated texts do not correspond to the originals. The application of the ProseRhythmDetector software tool significantly reduced the researchers' workload by automatically retrieving lexical and syntactic devices with a rather high accuracy (from 62 to 93% for different rhythmic devices).
引用
收藏
页码:697 / 711
页数:15
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