THE QUALITY OF THE TRANSLATION OF FRENCH LITERARY TEXTS USING THE DEEPL APPLICATION

The quality of the translation of French literary texts using the Deepl application: the impact of artificial intelligence on the translation field. Faced with the number of uses of machine translation software in a professional setting that takes a risk for translators, it seems essential to study the use of Deepl, a particular system that stands out from other machine translation services, including “artificial convolutional neural networks” (DeepL. 2017-2022.). This article explores the probability of this application being used by business services, which raises the following question: To what extent will the use of Deepl machine translation replace professional translators? It is assumed that this machine translation service could replace the tasks of professional literary translators at the intermediate level (A2 and B1). To test the hypothesis, the solving of the tasks was carried out on the basis of sampling methods and comparative analysis between literary texts at the intermediate (A2-B1) and advanced (B2-C1) level from French to Russian by the Deepl automatic translator. The materials for the analysis are as follows: “The little Nicholas of Sempé-Goscinny” (Chapter 1, A memory that we will cherish) adapted to level A2, “The exiles of Fabrice Coli” (Chapter 1, the happy days) adapted to level B1-B2 and “The riders of Joseph Kessel” (Chapter 1 -The ancestor of everyone, first page) adapted to level B2-C1. Many articles dedicated to the topic of translation have been read to make the interpretation consistent with the received data. It was essential to highlight the mistakes made by the automatic translator and the correction made by the post-editing for the analysis. The mistakes made by the automatic translator are the inaccurate structure, meaning and context to adapt to the interpretation of Russian readers. If technologies could certainly help linguists in their work, they probably could not replace them, but it is important to understand the algorithm of translation work for the functioning of intelligence to take advantage of it in the work of translators, which remains a contradictory topic for their future.

Авторы
Издательство
Российский университет дружбы народов (РУДН)
Язык
Французский
Страницы
484-495
Статус
Опубликовано
Год
2022
Организации
  • 1 Рeoples' Friendship University of Russia (RUDN University)
Ключевые слова
machine Translation; translation technology; DeepL; French foreign language; technologie de traduction; application Deepl; fle; traduction électronique
Дата создания
28.12.2023
Дата изменения
28.12.2023
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/99156/
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