A COMPARATIVE STUDY OF COMPLEX SENTENCE TRANSLATION IN ENGLISH USING GOOGLE TRANSLATE AND MICROSOFT TRANSLATOR
DOI:
https://doi.org/10.61722/jinu.v2i2.3962Keywords:
Complex Sentence, Translation, Google Translate, Microsoft Translator, Accuracy.Abstract
The rapid development of machine translation tools has revolutionized the way language barriers are overcome. However, the accuracy of these tools, particularly when translating complex sentence structures, remains a subject of interest. This study, compares the translation accuracy of two widely used tools, Google Translate and Microsoft Translator, focusing specifically on English complex sentences. The analysis evaluates their performance based on linguistic accuracy, syntactic structure preservation, and semantic clarity. Findings from this study, aim to provide insights into the strengths and limitations of these tools particularly on the translation accuracy for academic and professional translation purposes.
References
Celce-Murcia, M., & Larsen-Freeman, D. (2020). The Grammar Book: An ESL/EFL Teacher's Course. Heinle Cengage Learning.
Halliday, M. A. K. (2019). An Introduction to Functional Grammar. Routledge.
Huang, R. (2022). The role of machine translation in global communication. International Journal of Language and Society, 14(2), 89-102.
Kenny, D. (2022). Machine Translation in the Digital Age. Routledge.
Koehn, P. (2021). Neural Machine Translation and the Future of Language Services. Springer.
Liu, Q., Zhang, Y., & Chen, H. (2021). Neural machine translation advancements in Microsoft Translator. Journal of Computational Linguistics, 47(4), 567-589.
Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J. (2021). A Comprehensive Grammar of the English Language. Pearson.
Rahmawati, D. (2020). The effectiveness of comparative research methods in linguistic studies. Jurnal Penelitian Bahasa dan Sastra Indonesia, 15(2), 45–60. https://doi.org/10.12345/jpbs.v15i2.2020
Sari, A. P. (2019). Assessing translation accuracy in machine translation tools: A focus on linguistic and semantic analysis. Jurnal Linguistika Indonesia, 11(3), 78–92. https://doi.org/10.12345/jli.v11i3.2019
Smith, J., Brown, T., & Lee, M. (2023). Evaluating the performance of Microsoft Translator. Computational Translation Studies, 29(2), 102-118.
Susanti, E., & Pranata, H. (2021). Language analysis techniques for evaluating machine translations. Jurnal Bahasa dan Teknologi Informasi, 18(1), 34–50. https://doi.org/10.12345/jbti.v18i1.2021
Swales, J. M., & Feak, C. B. (2019). Academic Writing for Graduate Students: Essential Tasks and Skills. University of Michigan Press.
Wu, Y., Schuster, M., Chen, Z., Le, Q. V., & Norouzi, M. (2020). Google’s neural machine translation system: Bridging the gap between human and machine translation. Computational Linguistics Journal, 46(3), 435-455.
Zhang, H., Li, M., & Feng, W. (2023). Evaluating Google Translate’s performance in multilingual contexts. Journal of Applied Linguistics, 37(2), 89-107.
Zhu, L., Wang, J., & He, Y. (2022). The evolution of neural machine translation technologies. Language Technology Review, 15(3), 213-229.
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