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JOURNALS // Modelirovanie i Analiz Informatsionnykh Sistem // Archive

Model. Anal. Inform. Sist., 2019 Volume 26, Number 3, Pages 420–440 (Mi mais688)

This article is cited in 2 papers

Algorithms

Automated search of rhythm figures in a literary text for comparative analysis of originals and translations based on the material of the English and Russian languages

N. S. Lagutinaa, K. V. Lagutinaa, E. I. Boychukb, I. A. Vorontsovab, I. V. Paramonova

a P.G. Demidov Yaroslavl State University, Sovetskaya str., 14, Yaroslavl, 150003, Russia
b Yaroslavl State Pedagogical University named after K.D.Ushinsky, Respublikanskaya street, 108/1, Yaroslavl, 150000, Russia

Abstract: Analysis of the functional equivalence of an original text and its translation based on the achievement of rhythm equivalence is an extremely important task of modern linguistics. Moreover, the rhythm component is an integral part of functional equivalence that cannot be achieved without communication of rhythm figures of the text. To analyze rhythm figures in an original literary text and its translation, the authors developed the ProseRhythmDetector software tool that allows to find and visualize lexical and syntactic figures in English- and Russian-language prose texts: anaphora, epiphora, symploce, anadiplosis, epanalepsis, reduplication, epistrophe, polysyndeton, and aposiopesis. The goal of this work is to present the results of ProseRhythmDetector testing on two works by English authors and their translations into Russian: Ch. Bronte “Villette” and I. Murdoch “The Black Prince”. Basing on the results of the tool, the authors compared rhythm figures in an original text and its translation both in aspects of the rhythm and their contexts. This experiment made it possible to identify how the features of the author's style are communicated by the translator, to detect and explain cases of mismatch of rhythm figures in the original and translated texts. The application of the ProseRhythm-Detector software tool made it possible to significantly reduce the amount of linguists-experts work by automated detection of lexical and syntactic figures with quite high precision (from 62 % to 93 %) for various rhythm figures.

Keywords: text rhythm, rhythm analysis, natural language processing, rhythm figures, automation.

UDC: 004.912

Received: 12.08.2019
Revised: 11.09.2019
Accepted: 13.09.2019

DOI: 10.18255/1818-1015-420-440



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