مطالعۀ تطبیقی ترجمۀ زبان محاوره از فارسی به انگلیسی با استفاده از چت.جی.پی.تی و دیگر ابزار و ماشین های ترجمه
چکیده
ترجمۀ متون محاورهای بخشی از مشکلات در ترجمۀ متون ادبی است که میتواند به عنوان معیاری برای بررسی عملکرد ابزارها و ماشینهای ترجمه که اکثراً از هوش مصنوعی بهره میبرند، مورد استفاده قرار گیرد. به این منظور در تحقیق حاضر پنج سیستم اینترنتی ترجمه (Matecat, Yandex translator, ChatGPT, Microsoft Bing translate, Google Translate) انتخاب و توانایی آنها در ترجمۀ متون فارسی محاورهای بررسی شد. مقایسۀ این سیستمهای ترجمه برای پی بردن به نقاط ضعف آنها از دیگر اهداف این تحقیق بود که میتواند برای بهبود این سیستمها، به طراحان ماشینهای ترجمه و هوش مصنوعی کمک کند. در این راستا، 202 جمله یا عبارت حاوی 240 عبارت محاورهای فارسی به این پنج سیستم داده شد و ترجمههایی که آنها به زبان انگلیسی ارائه کردند با استفاده از معیارهای انتخابی، شامل درستی معنا، شناسایی عبارات محاورهای و انتقال درست لحن محاوره مورد بررسی قرار گرفت. برای نمره دادن به ترجمهها از مدل اورلاندو (2011) و برای تجزیه و تحلیل نتایج و مقایسه، از روش منطق فازی استفاده شد. در پایان مشخص شد سیستم ترجمۀ بینگ متعلق به مایکروسافت در ترجمۀ زبان فارسی محاورهای تواناتر است.
کلمات راهنما:
تعادل سبکی، زبان محاوره، ماشین ترجمه، منطق فازی، هوش مصنوعیمراجع
Aghai, M. (2024). ChatGPT vs. Google Translate: Comparative analysis of translation quality. Iranian Journal of Translation Studies, 22 (85), 87–103.
Akhrameev, S. (2015). MateCat review: Free online CaT tool for freelance translators. Medium.com. Retrieved April 16, 2024 from: https://medium.com/@RussianTranslatorPro/MateCat-review-free-online-cat-tool-for-freelance-translators-44e24663381.
Almahasees, Z. (2018). Assessment of Google and Microsoft Bing translation of journalistic texts. International Journal of Languages, Literature and Linguistics, 4 (3), 231–236.
Baldick, C. (2008). Oxford dictionary of literary terms. OUP
Bassnett, S. (2003). Estudos de tradução: Fundamentos de uma disciplina [Translation Studies: Fundamentals of a discipline. Translated by Vivina de Campos Figueiredo]. Lisbon: Fundação Calouste Gulbenkian
Bassnett, S. (2006). Writing and Translating. In S. Bassnet & P. Bush (Eds.), Translator as writer (pp. 173–183). Continuum.
Bassnett, S & Bush, P. (Eds.) (2006). Translator as writer. Continuum.
Bououden, R., & Saida, K. (2022). Comparing the effectiveness of Google Translate and MateCat tools in the translation of scientific texts from English into Arabic. In translation (في الترجمه), 9 (1), 543–560.
Bush, P. & Bassnett, S. (2006). Introduction. In S. Bassnet & P. Bush (Eds.), Translator as writer (pp. 1–8).Continuum.
Chochiang, K., Thongkhamdee, T., & Sathansat, L. (2020). Translation quality assessment of online translation systems in translating English to Thai on Phuket Tourism. Journal of Computer Science, 16(11), 1535–1545. https://doi.org/10.3844/jcssp.2020.1535.1545
Choudhury, S. (2023). Languages supported by ChatGPT and how to use it in other languages. MLYearning.org. Retrieved May 18, 2024 from: https://www.mlyearning.org/languages-supported-by-chatgpt/
Cornet, R., Hill, C., & De Keizer, N. (2017). Comparison of three English-to-Dutch machine translations of SNOMED CT procedures. PubMed, 245, 848–852. https://pubmed.ncbi.nlm.nih.gov/29295219
Frąckiewicz, M. (2023, April 5). The role of ChatGPT-3.5 in advancing machine translation and language localization. Ts2 Space. Retrieved April 10, 2024 from: https://ts2.space/en/the-role-of-chatgpt-3-5-in-advancing-machine-translation-and-language-localization/#gsc.tab=0
Hendy, A., Abdelrehim, M., Sharaf, A., Raunak, V., Gabr, M., Matsushita, H., Kim, Y. J., Afify, M. & Avadalla, H. H. (2023). How good are GPT models at machine Translation? A comprehensive evaluation. arXiv.org. Retrieved March 19, 2024 from: https://arxiv.org/abs/2302.09210
House, J. (1997). Translation quality assessment: A model revisited. Tübingen: G. Narr.
House, J. (2015). Translation quality assessment: Past and present. Routledge.
IBM. (n.d.). What is Natural Language Processing? IBM. Retrieved March 10, 2024 from: https://www.ibm.com/topics/naural-language-processing
OpenAI. (2022). Introducing ChatGPT. Retrieved March 2, 2024 from: https://openai.com/index/chatgpt/
Karjagdiu, L. & Mrasori, N. (2021). The role of literary translation in the development and enrichment of national Literature. Journal of Language and Linguistics Studies, 17(4), 2332–2345.
Khojasteh, H. A., Ansari, E., Bohlouli, M. (2020). LSCP: Enhanced Large Scale Colloquial Persian Language Understanding. arXiv.org. Retrieved May, 2024 from: https://arxiv.org/abs/2003.06499
Khoshafah, F. (2023). ChatGPT for Arabic-English Translation: Evaluating the Accuracy. europepmc.org. Retrieved March 15, 2024 from: https://europepmc.org/article/ppr/ppr645536
Liu, X., & Zhao, Y. (2015). The study on Quantitative Evaluation in the Translation Quality Management Based on the House’s Translation Quality Assessment Model. Advances in Social Science, Education and Humanities Research: Proceedings of the 2015 international conference on social science and technology education (April 2015). DOI: 10.2991/icsste-15.2015.250
Magueresse, A., Carles, V., & Heetderk, E. (2023). Low-resource languages: A review of past work and future challenges. ArXiv. Retrieved on February 25, 2024 from: https://www.semanticscholar.org/paper/Low-resourceLanguages%3AAReviewofPastWorkandMagueresseCarles/4de3595439ed8e433e1997b49ea9171c01dc846
MateCat. (n.d.). Main benefits for LSPs and freelance translators. MateCate.com. Retrieved on May 12, 2024 from: https://site.MateCat.com/benefits#:~:text=MateCat%20is%20an%20online%20CAT%20tool%20that%27s%20free%20and%20easy%20to%20use&text=It%20is%20and%20will%20always,Unlimited%20users%2C%20projects%20and%20storage
McCrimmon, J. M. (2022). Writing with a purpose [Short Edition]. Houghton Mifflin Company.
Mohan, K., & Skotdal, J. (2021). Microsoft Translator: Now translating 100 languages and counting! Microsoft.com. Retrieved March 25, 2024 from: https://www.microsoft.com/en-us/research/blog/microsoft-translator-now-translating-100-languages-and-counting/
Moltzau, A. (2020). The History of Google Translate. Medium. Retrieved May 23, 2024 from: https://alexmoltzau.medium.com/the-history-of-google-translate-fcbe9de3c10e
Musaad, D. M. M. A. M., & Al Towity, D. A. A. (2023). Translation Evaluation of Three Machine Translation Systems, with Special References to Idiomatic Expressions. مجلة العلوم التربوية و الدراسات الإنسانية [Humanities and Educational Science Journal], 29, 678–700. Retrieved from: https://hesj.org/ojs/index.php/hesj/article/view/700
Muzaffar, S., Behera, P., Jha, G. N., Hellan, L., & Beermann, D. (2017). The Concepts of Equivalence, Gain and Loss (Divergence) in English- URDU Web-Based Machine Translation Platforms. Proceedings of International Conference of South Asian Languages (ICOSAL-12) Retrieved February 12, 2024 from: https://scholar.google.co.kr/citations?view_op=view_citation&hl=ko&user=tekYvP0AAAAJ&citation_for_view=tekYvP0AAAAJ:MXK_kJrjxJIC
Orlando, M. (2014). Evaluation of translations in the training of professional translators. Interpreter and Translator Trainer, 5 (2) 293–308. Published online: 10 Feb 2014. https://doi.org/10.1080/13556509.2011.10798822
Patil, S & Davis, P. (2014). Use of Google Translate in medical communication: Evaluation of accuracy. British Medical Journal. doi: 10.1136/bmj.g7392 (Published 15 December 2014)
Rabiei, L., Rahmani, F., Khansari, M., Rajabi, Z., Salimi, M. (2023). Colloquial Persian POS (CPPOS) corpus: a novel corpus for Colloquial Persian part of speech tagging. ArXiv.org. Retrieved May 17, 2024 from: https://www.semanticscholar.org/paper/Colloquial-Persian-POS-(CPPOS)-Corpus%3A-A-Novel-for-Rabiei-Rahmani/8f4f06888d118d7ec10b3a03dd0160831cb89b89
Shamsfard, M. (2019). Challenges and Opportunities in Processing Low Resource Languages: A study on Persian. Proceedings of the Language Technologies for All (LT4All), pages 291–295. Paris, UNESCO Headquarters, 5–6 December, 2019.
Sholevar, B. (1974). Khashm-o-Hayahoo [Sound and Fury]. Tehran: Pyrooz Publishing House.
Siu, S. C. (2023). ChatGPT and GPT-4 for Professional Translators: Exploring the Potential of Large Language models in translation. Social Science Research Network. Retrieved January 19, 2024 from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4448091. https://doi.org/10.2139/ssrn.4448091
Silveira Brisolara, V. (2011). The translator as an Author. Nonada: Letras em Revista, 1 (16), 107–125.
Stap, D. & Araabi, A. (2023). ChatGPT is not a good indigenous translator. Proceedings of the Workshop on Natural Language Processing for Indigenous Languages of the Americas. (Published in AMERICASNLP 2023). url: https://api.semanticscholar.org/CorpusID:259833859
Sumasjo, H. P., Mahanani, M. P. (2020). Analysis of Yandex Translate translation quality of new items from Indonesian to English. The Asian Journal of English Language and Pedagogy, 8 (1), 1–7. Retrieved February 22, 2024 from: https://ejournal.upsi.edu.my/index.php/AJELP/article/view/3096
Sutrisno, A. (2020). The accuracy and shortcomings of Google Translate translating English sentences to Indonesian. Education Quarterly Reviews, 3(4), 555–568. https://doi.org/10.31014/aior.1993.03.04.161
Timothy, M. (2023). ChatGPT vs. Google Translate: Which Is Better At Translation? MUO. Retrieved February 14, 2024 from: https://www.makeuseof.com/chatgpt-vs-google-translate-which-is-better-at-translation/
Turovsky, B. (2016). Ten years of Google Translate. Google. Retrieved May 4, 2024 from: https://blog.google/products/translate/ten-years-of-google-translate/
Yandex AI. (n.d.). Bridging the Language gap with Neural Translation of Videos, Images and Text. Retrieved February 15, 2024 from: https://ai.yandex.com/blog/neural-translation
فاکنر، ویلیام. .1353.خشم و هیاهو. ترجمه بهمن شعله ور. انتشارات پیروز.
Downloads
چاپشده
ارجاع به مقاله
شماره
نوع مقاله
DOR
مجوز
حق نشر 2024 Zeynab Mirhashemi, Mahvash Gholami, Hossein Bhari
این پروژه تحت مجوز بین المللی Creative Commons Attribution-NonCommercial 4.0 می باشد.
Copyright Licensee: Iranian Journal of Translation Studies. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0 license).