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

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 linguistsexperts work by automated detection of lexical and syntactic figures with quite high precision (from 62 % to 93 %) for various rhythm figures.

1. Golyakova L. A., “Ritm hudozhestvennogo proizvedeniya: kommunikativno-pragmaticheskij aspekt”, Vestnik Permskogo universiteta. Rossijskaya i zarubezhnaya filologiya, 2011, № 3, 94–99, (in Russian).

2. Golubeva-Monatkina N. I., “K probleme ritma prozy”, Izvestiya Rossijskoj akademii nauk. Seriya literatury i yazyka, 76:2 (2017), 16–27, (in Russian).

3. Golubeva-Monatkina N. I., “O ritme hudozhestvennoj prozy v svete idej M. M. Bahtina i perevode”, Russkij yazyk i kul’tura v zerkale perevoda, 2016, № 1, 105–113, (in Russian).

4. Ivanova-Luk’yanova G. N., “Ritm prozy v real’nosti i vospriyatii”, Trudy Instituta russkogo yazyka im. V. V. Vinogradova, 7:7 (2016), 365–382, (in Russian).

5. Fenenko N. A., “Lingvokul’turnaya adaptaciya teksta pri perevode: predely vozmozhnogo i dopustimogo”, Vestnik Voronezhskogo gosudarstvennogo universiteta. Seriya: Lingvistika i mezhkul’turnaya kommunikaciya, 1:7 (2001), 70–75, (in Russian).

6. Delmonte R., “Computing Poetry Style”, Proceedings of 1st International Workshop ESSEM 2013/ CEUR Workshop Proc., 2013, 148–155.

7. Bobenhausen K., Hammerich B., “Literary metrics, Linguistic metrics, and the algorithmic analysis of German poetry using Metricalizer (2)”, Langages, 2015 3, 67–88.

8. Niculescu I., Trausan-Matu S., “Rhythm analysis of texts using Natural Language Processing”, RoCHI, 2016, 107–112.

9. Niculescu I., Trausan-Matu S., “Rhythm analysis in chats using Natural Language Processing”, RoCHI, 2017, 69–74.

10. Kishalova L. V., “Analiz osobennostej ritmicheskoj struktury tekstov raznyh stilej rechi”, Vestnik Bryanskogo gosudarstvennogo universiteta, 2016, № 1 (27), 257–261, (in Russian).

11. Boychuk E. et al., “Automated approach for rhythm analysis of French literary texts”, Proceedings of 15th Conference of Open Innovations Association FRUCT, IEEE, 2014, 15–23.

12. Damasevicius R., Kapociute-Dzikiene J., Wozniak M., “Towards Rhythmicity analysis of text using empirical mode decomposition”, Proceeding of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 1, IC3K, 2017, 310–317.

13. Kelly A. R. et al., “Toward an ontology of rhetorical figures”, Proceedings of the 28th ACM International Conference on Design of Communication, ACM, 2010, 123–130.

14. Hromada D. D., “Initial experiments with multilingual extraction of rhetoric figures by means of PERL-compatible regular expressions”, Proceedings of the Second Student Research Workshop associated with RANLP 2011, 2011, 85–90.

15. Toldova S. et al., “Error analysis for anaphora resolution in Russian: new challenging issues for anaphora resolution task in a morphologically rich language”, Proceedings of the Workshop on Coreference Resolution Beyond OntoNotes, 2016, 74–83.

16. Dubremetz M., Nivre J., “Rhetorical Figure Detection: Chiasmus, Epanaphora, Epiphora”, Frontiers in Digital Humanities, 5, 2018.