Keywords
generativ AI
milliy-madaniy konnotatsiya
ingliz tili
o‘zbek tili
tarjima transformatsiyasi
konnotativ ma’no
How to Cite
Abstract
Mazkur maqolada ingliz-o‘zbek va o‘zbek-ingliz yo‘nalishidagi generativ sun’iy intellekt tarjimasida milliy-madaniy konnotatsiyaning saqlanishi, neytrallashuvi va yo‘qolishi masalalari lingvistik hamda pragmatik nuqtayi nazardan tahlil qilinadi. Tadqiqotda milliy-madaniy xususiyatga ega leksik birliklar, realiyalar, urf-odat va marosim nomlari, ijtimoiy munosabatlarni ifodalovchi birliklar, mehmondo‘stlik, qarindoshlik, milliy taom va turmush tarziga oid so‘z hamda birikmalar asosiy material sifatida tanlandi. Generativ AI tarjimasida manba birlikning denotativ ma’nosi ko‘pincha saqlansa-da, uning tarixiy, assotsiativ, emotsional, aksiologik va pragmatik komponentlari turli darajada o‘zgarishi aniqlandi.References
1. Baker, M. (2018). In Other Words: A Coursebook on Translation. 3rd ed. London and New York: Routledge.
2. Bassnett, S. (2014). Translation Studies. 4th ed. London and New York: Routledge.
3. Catford, J. C. (1965). A Linguistic Theory of Translation: An Essay in Applied Linguistics. London: Oxford University Press.
4. House, J. (2015). Translation Quality Assessment: Past and Present. London and New York: Routledge.
5. Katan, D. (2014). Translating Cultures: An Introduction for Translators, Interpreters and Mediators. 2nd ed. London and New York: Routledge.
6. Koehn, P. (2020). Neural Machine Translation. Cambridge: Cambridge University Press.
7. Newmark, P. (1988). A Textbook of Translation. New York: Prentice Hall.
8. Nida, E. A. (1964). Toward a Science of Translating: With Special Reference to Principles and Procedures Involved in Bible Translating. Leiden: E. J. Brill.
9. Nida, E. A., Taber, C. R. (1969). The Theory and Practice of Translation. Leiden: E. J. Brill.
10. O‘Brien, S. (2012). Translation as human-computer interaction. Translation Spaces, 1, 101-122.
11. Sutskever, I., Vinyals, O., Le, Q. V. (2014). Sequence to sequence learning with neural networks. Advances in Neural Information Processing Systems, 27, 3104- 3112.
12. Toral, A., Way, A. (2018). What level of quality can neural machine translation attain on literary text? In J. Moorkens et al. (Eds.), Translation Quality Assessment: From Principles to Practice. Cham: Springer, 263-287.
13. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30.
14. Venuti, L. (2018). The Translator’s Invisibility: A History of Translation. 3rd ed. London and New York: Routledge.
15. Vinay, J.-P., Darbelnet, J. (1995). Comparative Stylistics of French and English: A Methodology for Translation. Amsterdam and Philadelphia: John Benjamins.
16. Vlahov, S., Florin, S. (1980). Neperevodimoe v perevode. Moscow: Mezhdunarodnye otnosheniya.
17. Wierzbicka, A. (1997). Understanding Cultures through Their Key Words: English, Russian, Polish, German, and Japanese. New York: Oxford University Press.
This work is licensed under a Creative Commons Attribution 4.0 International License.