Implementation and modernisation of the master’s degree programme “Computer-assisted and machine translation technology”

Authors

  • Maxim V. Berendyaev Northern (Arctic) Federal University
  • Elena S. Kokanova Northern (Arctic) Federal University https://orcid.org/0000-0001-6623-5636
  • Nikolay Yu. Kulikov Northern (Arctic) Federal University

DOI:

https://doi.org/10.33910/2686-830X-2024-6-1-60-65

Keywords:

augmented translator, artificial intelligence, Master’s degree programme, computer-assisted and machine translation technology, professional competence

Abstract

The awareness of possibilities and limitations of artificial intelligence in translation is becoming an integral part of professional competence. Training an “augmented translator” in this context is a complex task. This article provides an example of the implementation and modernisation of the innovative Master’s degree programme “Computer-Assisted and Machine Translation Technology” at the Department of Translation Technology and Practice at “AKM-West” of Northern (Arctic) Federal University (Arkhangelsk, Russia). The article considers current approaches to translator training at the university, fields of research work by master’s degree students, ways of modernising the Master’s degree programme. They depend on the requirements of the labour market, technological development and scientific research, changes in competence frameworks, as well as local factors (potential local clients, potential applicants, etc.). The participation of the professional community in the implementation of the Master’s degree programme contributes to career adaptability to today’s translation and localization industry. The organisation of scientific meetings for students (for example, the annual All-Russian Youth Scientific Conference “Modern Technologies in Translation. From Machine Translation to Machine Learning: Stereotypes and New Opportunities”, the section “Augmented translation: human being + machine” in the Arkhangelsk conference of young scientists “LANGUAGE. CULTURE. LITERATURE”) and the publication of a collection of papers by young scientists (for example, “From Machine Translation to Machine Learning”) can help to participate in the promotion of science and knowledge about modern translation technology in the Russian language. An interdisciplinary approach, a practice-oriented approach, a research approach and a professional orientation help to ensure the training of “augmented translators” who are able to get a successful career in the modern world.

References

ЛИТЕРАТУРА

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Full-time academic position in translation and artificial intelligence (2024) ScholarshipDb.Net. [Online]. Available at: https://scholarshipdb.net/jobs-in-Belgium/Full-Time-Academic-Position-In-Translation-And-Artificial-Intelligence-Universit-Libre-De-Bruxelles-Ulb=c0u43uLB7hGUYwAlkGUTnw.html (accessed 14.02.2024).

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Kokanova, E. S., Epimakhova, A., Berendyaev, M. et al. (2021) Traduction automatique, un nouveau défi pour la formation des traducteurs: Le cas de l’Université fédérale Arctique (Russie). In: J.-C. Beacco, J. C. Herreras, C. Tremblay (eds.). La traduction automatique et les usages sociaux des langues. Quelles conséquences pour la diversité linguistique? Sainte Luce sur Loire: Bookelis Publ., pp. 101–114. https://doi.org/10.3917/oep.beacc.2021.01.0101

Kokanova, E. S., Lyutyanskaya, M., Epimakhova, A. (2023) Is it difficult to launch a pioneering master’s program in translation? In: Human translation and natural language processing towards a new consensus? Venezia: Edizioni Ca’ Foscari Publ., pp. 115–121. http://dx.doi.org/10.30687/978-88-6969-762-3/008

Raunak, V., Sharaf, A., Wang, Y. et al. (2023) Leveraging GPT-4 for automatic translation post-editing. In: H. Bouamor, J. Pino, K. Bali (eds.). Findings of the association for computational linguistics: EMNLP 2023. Singapore: Association for Computational Linguistics Publ., pp. 11994–12009. https://doi.org/10.48550/arXiv.2305.14878

REFERENCES

Feng, Y., Qiang, J., Li, Y. et al. (2023) Sentence simplification via large language models. ArXiv.org. [Online]. Available at: https://arxiv.org/pdf/2302.11957.pdf (accessed 24.01.2024). (In English)

Full-time academic position in translation and artificial intelligence (2024) ScholarshipDb.Net. [Online]. Available at: https://scholarshipdb.net/jobs-in-Belgium/Full-Time-Academic-Position-In-Translation-And-Artificial-Intelligence-Universit-Libre-De-Bruxelles-Ulb=c0u43uLB7hGUYwAlkGUTnw.html (accessed 14.02.2024). (In English)

Grisot, J. (2020) 3 ways you can become an ‘augmented translator’. RWS Blog. [Online]. Available at: https://www.rws.com/blog/augmented-translator/ (accessed 14.02.2024). (In English)

EMT competence framework (2022) European Commission. [Online]. Available at: https://commission.europa.eu/document/download/b482a2c0-42df-4291-8bf8-923922ddc6e1_en?filename=emt_competence_fwk_2022_en.pdf (accessed 24.01.2024). (In English)

Kokanova, E. S., Epimakhova, A., Berendyaev, M. et al. (2021) Traduction automatique, un nouveau défi pour la formation des traducteurs: Le cas de l’Université fédérale Arctique (Russie) [Machine translation, a new challenge for the training of translators: the case of the Arctic Federal University (Russia)]. In: J.-C. Beacco, J. C. Herreras, C. Tremblay (eds.). La traduction automatique et les usages sociaux des langues. Quelles conséquences pour la diversité linguistique? [Machine translation and the social uses of languages. What are the consequences for linguistic diversity?]. Sainte Luce sur Loire: Bookelis Publ., pp. 101–114. https://doi.org/10.3917/oep.beacc.2021.01.0101 (In French)

Kokanova, E. S., Lyutyanskaya, M., Epimakhova, A. (2023) Is it difficult to launch a pioneering master’s program in translation? In: Human translation and natural language processing towards a new consensus? Venezia: Edizioni Ca’ Foscari Publ., pp. 115–121. http://dx.doi.org/10.30687/978-88-6969-762-3/008 (In English)

Kokanova, E. S., Svetova, S. Yu., Berendyaev, M. V. et al. (2023) Obuchenie postredaktirovaniyu mashinnogo perevoda v vuze [Training in post-editing machine translation at the university]. In: L. Yu. Shchipitsina (ed.) Razvitie Severa i Arktiki: potentsial nastavnichestva i innovatsii v sotsial’no-gumanitarnoj sfere: materialy XI Vserossijskoj nauchno-prakticheskoj konferentsii s mezhdunarodnym uchastiem [Development of the North and the Arctic: The potential for mentoring and innovation in the humanities and social studies: Proceedings of the International scientific conference with international participation]. Arkhangelsk: Northern (Arctic) Federal University named after M. V. Lomonosova Publ., pp. 269–272. (In Russian)

Raunak, V., Sharaf, A., Wang, Y. et al. (2023) Leveraging GPT-4 for automatic translation post-editing. In: H. Bouamor, J. Pino, K. Bali (eds.). Findings of the association for computational linguistics: EMNLP 2023. Singapore: Association for Computational Linguistics Publ., pp. 11994–12009. https://doi.org/10.48550/arXiv.2305.14878 (In English)

Sostoyalas’ IV Vserossijskaya molodezhnaya nauchnaya konferentsiya “Sovremennye tekhnologii v perevode. Ot mashinnogo perevoda k mashinnomu obucheniyu: stereotipy i novye vozmozhnosti” v ramkakh vserossijskogo konkursa “Moya professiya — IT” [The IV All-Russian youth scientific conference “Modern technologies in translation. from machine translation to machine learning: Stereotypes and new opportunities” was held as part of the All-Russian contest “My profession is IT”] (2023) Novosti Vysshej shkoly sotsial’no-gumanitarnykh nauk i mezhdunarodnoj kommunikatsii [News of Graduate School of Social Sciences, Humanities and International Communication], 30 October. [Online]. Available at: https://narfu.ru/hssshic/novosti/all/384295/ (accessed 02.02.2024). (In Russian)

Published

2024-09-27

Issue

Section

Reports, Reviews, Personalities