Aplicação de sistemas de tradução automática utilizando ferramentas de inteligência artificial para a formação de estudantes universitários em tradução escrita

Aliya Abdrakhmanova; Marina Vinnikova; Elena Semushina; Guzel Fassakhova; Liliya Islamova; Elena Slepneva

doi:10.22633/rpge.v29i00.20793

Authors

Aliya Abdrakhmanova Kazan Federal University https://orcid.org/0000-0002-9453-8981
Marina Vinnikova Kazan Federal University https://orcid.org/0000-0003-3070-8467
Elena Semushina Kazan Federal University https://orcid.org/0000-0002-7453-5695
Guzel Fassakhova Kazan State Agrarian University https://orcid.org/0000-0002-0590-395X
Liliya Islamova Kazan State Agrarian University https://orcid.org/0000-0002-5981-9518
Elena Slepneva Kazan National Research Technological University https://orcid.org/0000-0001-6489-8700

DOI:

https://doi.org/10.22633/rpge.v29i00.20793

Keywords:

Machine translation (MT), Automated translation (AT), CAT system, Artificial intelligence (AI), Translation training

Abstract

This article examines the features and prospects of using artificial intelligence (AI) tools in written translation and translation training in higher education institutions. The study aims to provide a theoretical and practical justification for modern trends in AI technology development within translation activities. The article identifies the prerequisites for AI technology application and presents a comparative analysis of AI tools in written translation. Through a comparative study, the characteristics of automated translation systems (CAT) in written translation—namely Trados, SmartCAT, and MemoQ—were described. The study analyzed CAT system indicators such as functional capabilities, software availability for installation, ease of use for beginners or student translators, and the clarity of the user interface. The comparative analysis of CAT systems like Trados, SmartCAT, and MemoQ demonstrated that student translators should use these tools in written translation only after mastering the basic skills of more user-friendly programs, particularly the cloud-based SmartCAT system. SmartCAT, while matching Trados Studio and MemoQ in functionality, offers an intuitive learning experience, as it includes a built-in translation training system—an important advantage for beginner translators. The article also identifies the challenges of mastering CAT translation systems and outlines their future development prospects.

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Author Biographies

Aliya Abdrakhmanova, Kazan Federal University

Kazan Federal University, Kazan – Russia. Candidate of Sciences, Associate Professor at Department of Practice and Theory of Translation.

Marina Vinnikova, Kazan Federal University

Kazan Federal University, Kazan – Russia. Candidate of Sciences, Associate Professor at Department of Practice and Theory of Translation.

Elena Semushina, Kazan Federal University

Kazan Federal University, Kazan – Russia. Candidate of Sciences, Associate Professor at Department of Practice and Theory of Translation.

Guzel Fassakhova, Kazan State Agrarian University

Kazan State Agrarian University, Kazan – Russia. Candidate of Sciences, Associate Professor at Department of Foreign Languages.

Liliya Islamova, Kazan State Agrarian University

Kazan State Agrarian University, Kazan – Russia. Senior Teacher at the Department of Foreign Languages.

Elena Slepneva, Kazan National Research Technological University

Kazan National Research Technological University, Kazan – Russia. Candidate of Sciences, Associate Professor at Department of Service Technologies.

References

Alfuraih, R. F. (2020). The undergraduate learner translator corpus: A new resource for translation studies and computational linguistics. Language Resources and Evaluation, 54(3), 801–830. https://doi.org/10.1007/s10579-019-09472-6

Appakova-Shogina, N., Kondratiev, K., Saykina, G., & Shammazova, E. (2024). Digital socialization in the educational environment: Hermeneutics of subjectivity. Revista Conrado, 20(101), 134–140.

Arcan, M., Turchi, M., Tonelli, S., & Buitelaar, P. (2017). Leveraging bilingual terminology to improve machine translation in a CAT environment. Natural Language Engineering, 23(5), 763–788. https://doi.org/10.1017/S1351324917000195

Besschetnova, O., Tsyglakova, E., & Vikulov, A. (2024). Internet addiction and network identity: Development characteristics in young students. Educação & Formação, 9, e14244. https://doi.org/10.25053/redufor.v9.e14244

Bowker, L. (2019). Machine translation literacy: Academic libraries' role. Proceedings of the Association for Information Science and Technology, 56(1), 618–619. https://doi.org/10.1002/pra2.108

Brynjolfsson, E., Hui, X., & Liu, M. (2019). Does machine translation affect international trade? Evidence from a large digital platform. Management Science, 65(12), 5449–5460. https://doi.org/10.1287/mnsc.2019.3388

Çetiner, C. (2018). Analyzing the attitudes of translation students towards CAT (computer-aided translation) tools. Journal of Language and Linguistic Studies, 14(1), 153–161.

El-Rahman, S. A., El-Shishtawy, T. A., & El-Kammar, R. A. (2018). A knowledge-based machine translation using AI technique. International Journal of Software Innovation, 6(3), 79–92. https://doi.org/10.4018/IJSI.2018070106

Garbovsky, N. K., & Kostikova, O. I. (2019). Intellekt dlya perevoda: Iskusnyy ili iskusstvennyy? [Intelligence in translation: Artful and artificial?]. Moscow University Translation Studies Bulletin, (4), 3–25.

Gudkov, N. N. (2022). Iskusstvennyy intellekt vs lichnost' perevodchika: Problema zameny zhivogo spetsialista tekhnologiyami budushchego v oblasti perevoda [Artificial intelligence vs. the translator’s personality: The problem of replacing human specialists with future translation technologies]. In Aktual'nyye problemy pedagogiki, psikhologii i perevodovedeniya (pp. 188–195). Asterion.

Han, B. (2020). Translation, from pen-and-paper to computer-assisted tools (CAT tools) and machine translation (MT). Proceedings, 63(1), 56. https://doi.org/10.3390/proceedings2020063056

Juan, L., & Yahaya, N. B. (2019). Research on the application of computer-aided translation to translation teaching. International Journal of Academic Research in Progressive Education and Development, 8(4), 795–804. https://doi.org/10.6007/ijarped%2Fv8-i4%2F6722

Karlgren, K., Lakkala, M., Toom, A., Ilomäki, L., Lahti-Nuuttilla, P., & Muukkonen, H. (2020). Assessing the learning of knowledge work competence in higher education: Cross-cultural translation and adaptation of the Collaborative Knowledge Practices Questionnaire. Research Papers in Education, 35(1), 8–22. https://doi.org/10.1080/02671522.2019.1677752

Karpińska, P. (2017). Computer-aided translation: Possibilities, limitations and changes in the field of professional translation. Journal of Education Culture and Society, 2, 133–142. https://doi.org/10.15503/jecs20172.133.142

Kashkin, V., & Haladay, D. J. (2024). Automated text analysis methods to identify the individual structure of motivation for sports and a healthy lifestyle. BIO Web of Conferences, 120, 01044. https://doi.org/10.1051/bioconf/202412001044

Kolin, K. K., Khoroshilov, A. A., Nikitin, Y. V., & Pshenichny, S. I. (2021). Iskusstvennyy intellekt v tekhnologiyakh mashinnogo perevoda [Artificial intelligence in machine translation technologies]. Social Innovations and Social Sciences, (2), 64–80. https://doi.org/10.31249/snsn/2021.02.05

Kubrak, V. (2023). Limitations of the scope of exclusive rights in relation to results created using artificial intelligence technologies. Legal Bulletin, 3(7), 121–129. https://doi.org/10.5281/zenodo.11189432

Levit, D. (2024). The legal regime of the results created by artificial intelligence technologies. Legal Bulletin, 2(9), 108–119. https://doi.org/10.5281/zenodo.12683332

Litwinowa, M., Gasanbekov, S., Lawrencenko, S., Shtukareva, E., Borodina, M., & Golubeva, T. (2022). Improving the stylistic and grammar skills of future translators, depending on the use of electronic editors and methods of working with the text in the translation process. Revista Conrado, 18(86), 125–130.

Osipov, M. Y. (2023). K voprosu ob osobennostyakh formulirovaniya i ispol'zovaniya testa T'yuringa dlya Chat GPT [On the question of the specifics of the formulation and use of the Turing test for ChatGPT]. Programmnyye sistemy i vychislitel'nyye metody, (4), 1–16. https://doi.org/10.7256/2454-0714.2023.4.68680

Pankratova, A. V. (2023). Problema dizayna kak metayazyka informatsionnogo prostranstva [The problem of design as a metalanguage of the information space]. Culture and Art, (12), 1–11. https://doi.org/10.7256/2454-0625.2023.12.68776

Parsa, R. N. (2021). Trends in e-tools and resources for translators and interpreters. Translation & Interpreting, 13(2), 183–186. https://doi.org/10.12807/ti.113202.2021.r01

Rarenko, M. B. (2021). Machine translation: From “rule-based translation” to neural translation (review). Social and Human Sciences: Domestic and Foreign Literature, (3), 70–79.

Safiullin, M., Gataullina, A., & Yelshin, L. (2024). Comparative analysis of higher education and science in Russia and Japan: Key development features. Revista Conrado, 20(101), 187–197.

Sultonova, L., Vasyukov, V., & Kirillova, E. (2023). Concepts of legal personality of artificial intelligence. Lex Humana, 15(3), 283–295. Retrieved from https://seer.ucp.br/seer/index.php/LexHumana/article/view/2596

Thawabteh, M. A. (2018). Complementarity between translation memories and computer-aided translation tools: Implications for translator training. SKASE Journal of Translation and Interpretation, 11(2), 2–15.

Ukolova, L. I., & Afanasyev, V. V. (2023). Pedagogical potential of the application of computer educational programs in fine arts lessons. Anthropological Didactics and Upbringing, 6(1), 21–30.

Vandepitte, S., & Lefever, E. (2018). Translation as a multilingual activity in the digital era. Revue française de linguistique appliquée, 23(2), 59–72. https://doi.org/10.3917/rfla.232.0059

Xu, Y. (2020). The application and practice of computer-aided translation in English teaching. Computer-Aided Design & Applications, 20(12), 216–230.

Zhilkibaeva, R., Avazova, S., Qahhorova, M., Myrksina, Y., & Tretyak, E. (2024). Impact of cloud technology implementation in the educational process. Revista Conrado, 20(99), 387–392.