A SEMANTIC ANALYSIS OF COMMON ERRORS: EVALUATING THE LIMITS OF ONLINE TRANSLATION APPLICATIONS
DOI:
https://doi.org/10.56983/eltm.v4i3.1746Keywords:
Translation Application, Semantic Analysis, Translation ErrorsAbstract
This article examines the evaluation of translation errors made by using online translation applications. Online translation applications are increasingly important for cross-language communication, but their quality often contains errors and defects. The research uses qualitative methods with a descriptive analysis approach, focusing on sixth-semester English students at the Indonesian Christian University of Toraja. The study consists of 10 Indonesian sentences translated into English using an online translation application. The results of semantic analysis show significant translation errors, including context-related errors, loss of nuance, and word choice errors. Inconsistencies in translation between sentences are also observed. The article emphasizes the importance of human skills in translation and double-checking translation results. It emphasizes the need for a deeper understanding of context and nuance. While online translation apps can be useful tools, careful and critical evaluation is still essential to ensure optimal quality in cross-language communication.
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References
Allen, J. (1995). Natural Language Understanding. Benjamin-Cummings Publishing Co.
Arnold, D., Balkan, L., Meijer, S., Humphreys, R., & Sadler, L. (1994). Machine Translation: An Introductory Guide. NCC Blackwell.
Baker, M. (2011). In Other Words: A Coursebook on Translation (2nd ed.). Routledge.
Baldwin, T., & Kim, S. N. (2010). Multiword expressions. In Handbook of Natural Language Processing (2nd ed.). Chapman & Hall/CRC.
Bentivogli, L., Bisazza, A., Cettolo, M., & Federico, M. (2016). Neural Versus Phrase-Based Machine Translation Quality: A Case Study. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 257–267.
Catford, J. C. (1965). A Linguistic Theory of Translation: An Essay in Applied Linguistics. Oxford University Press.
Creswell, J. W. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (3rd ed.). SAGE Publications.
Crystal, D. (2003). English as a global language. Cambridge University Press.
Díaz-Cintas, J., & Remael, A. (2020). Audiovisual Translation: Subtitling (2nd ed.). Routledge.
Federico, M., Bertoldi, N., & Cettolo, M. (2008). Irstlm: an open source toolkit for handling large scale language models. INTERSPEECH 2008.
House, J. (2015). Translation Quality Assessment: Past and Present. Routledge.
Hutchins, J. (2003). Machine Translation and Computer-based Translation Tools: What’s Available and How It’s Used. A New Spectrum of Translation Studies, March, 13–48. https://aclanthology.org/www.mt-archive.info/05/ISMTCL-2009-Hutchins.pdf
Hutchins, J. (2005a). Current commercial machine translation systems and computer-based translation tools: system types and their uses. International Journal of Translation, 17(1–2), 5–38.
Hutchins, J. (2005b). The history of machine translation in a nutshell. Language Today, 1(2), 30–36.
Hutchins, W. J., & Somers, H. L. (1992). An Introduction to Machine Translation. Academic Press.
Jurafsky, D., & Martin, J. H. (2009). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2nd ed.). Pearson Prentice Hall.
Koehn, P. (2010). Statistical Machine Translation. Cambridge University Press.
Liu, M., & Zhang, X. (2020). A Survey of Evaluation Metrics for Machine Translation. Journal of Computer Science and Technology, 35(4), 825–844.
Lo, C. (2019). YiSi - A Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources. Proceedings of the Fourth Conference on Machine Translation, 507–515.
Manning, C. D., & Schütze, H. (1999). Foundations of Statistical Natural Language Processing. MIT Press.
Munday, J. (2016). Introducing Translation Studies: Theories and Applications. Routledge.
Newmark, P. (1988). A Textbook of Translation. Prentice Hall International.
Nida, E. A., & Taber, C. R. (1982). The Theory and Practice of Translation. Brill.
Nord, C. (1997). Translating as a Purposeful Activity: Functionalist Approaches Explained. St. Jerome Publishing.
O’Brien, S. (2012). Machine Translation and Translation Technology. Routledge.
Pustejovsky, J. (1995). The Generative Lexicon. MIT Press.
Pym, A. (2010). Exploring Translation Theories. Routledge.
Sennrich, R., & Haddow, B. (2016). Linguistic Input Features for Neural Machine Translation. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 102–111.
Siumarlata, V., & Sallata, Y. N. (2024). Practical Translation 1. Deepublish.
Siumarlata, V., Sallata, Y. N., & Rachel. (2024). TRANSLATION APPLICATIONS IN EFL CLASSROOM: INSIGHTS FROM STUDENT PERCEPTIONS. English Language Teaching Methodology, 4(2), 282–294. https://doi.org/https://doi.org/10.56983/eltm.v4i2.1541
Specia, L., & Farzindar, A. (2010). Machine translation of idioms and culture-specific content: The case of French-English. The Prague Bulletin of Mathematical Linguistics, 93, 17–26.
Torres, L., & Coto, E. (2018). Assessing Machine Translation Quality: A Comprehensive Review. Language Resources and Evaluation, 52(1), 169–200.
Turner, A. (2021). Lost in translation: How machine translation struggles with idioms. Journal of Artificial Intelligence Research, 70, 635–670.
Urlaub, P., & Dessein, E. (2022). Machine translation and foreign language education. Frontiers in Artificial Intelligence, 5:936111. https://doi.org/936111. doi: 10.3389/frai.2022.936111
Venuti, L. (2008). The Translator’s Invisibility: A History of Translation (2nd ed.). Routledge.
Wu, Y., Schuster, M., Chen, Z., Le, Q. V., Norouzi, M., Macherey, W., & Dean, J. (2016). Google’s neural machine translation system: Bridging the gap between human and machine translation. ArXiv Preprint ArXiv:1609.08144.
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