A COMPARATIVE ANALYSIS OF ACCURACY BETWEEN GOOGLE TRANSLATE AND BARD IN TRANSLATING ABSTRACTS OF SCIENTIFIC JOURNALS
Keywords:
translation, accuracy, google translate, bard
Abstract
The accuracy of machine translation is still debatable. This study aims to compare the accuracy of Google Translate and BARD in translating scientific journal abstracts. The main focus is to evaluate the extent to which these two platforms can preserve the meaning and quality of translation in the abstracts of Adabiyyāt journal. This research utilizes two main theories in evaluating translation accuracy, namely the Human-mediated Translation Edit Rate (HTER) by Snover (2006) to identify translation errors and the Translation Quality Index (TQI) by Schiaffino & Zearo (2005) to calculate overall accuracy results. The results of this study show that GT is proven to be more accurate than Bard in translating abstracts from scientific journals. This can be seen from the final result of GT's calculation, which is greater than that of Bard. GT scored 99,7% in total, while Bard only got 99,1%.
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Baharuddin, Baharuddin, et al. "Penerapan Teori Terjemahan pada Editing Hasil Terjemahan Google Translate pada Teks Akademik oleh Mahasiswa Universitas Mataram." Jurnal Ilmiah Profesi Pendidikan, vol. 6, no. 4, Dec. 2021, pp. 816-824, doi:10.29303/jipp.v6i4.390.
Baharuddin, B., Amin, M., Thohir, L., & Wardana, L. A. (2021). Penerapan Teori Terjemahan pada Editing Hasil Terjemahan Google Translate pada Teks Akademik oleh Mahasiswa Universitas Mataram. Jurnal Ilmiah Profesi Pendidikan, 6(4), 816-824.
Brahmana, C. R. S, Sofyan, R., & Putri, D. M. (2020). Problems in the application of Google Translate as a learning media in translation. Language Literacy: Journal of Linguistics, Literature, and Language Teaching, 4(2), 384–389. https://doi.org/10.30743/ll.v4i2.2893
Brookshire, R. H., & Brundage, S. B. (2015). Writing Scientific Research in Communication Sciences and Disorder. Plural Publishing.
DAO, X.-Q. (2023). Which large language model should you use in Vietnamese education: Chatgpt, Bing Chat, or Bard? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4527476
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4.
Fitria, T. N. (2018). Translation Techniques Found in English to Indonesian Abstract Translation of Journal Edunomika 2018. ELITE Journal Volume 05 Number 2
Fitria, T. N. (2020). Error Analysis of English Abstract in International Journal of Economics, Business and Accounting Research (IJEBAR). Al-Lisan: Jurnal Bahasa (e-Journal), 5.
Fitria, T. N. (2021). A review of machine translation tools: The translation’s ability. Language Circle: Journal of Language and Literature, 16(1), 162–176. https://doi.org/10.15294/lc.v16i1.30961
Ghasemi, H., & Hashemian, M. (2016). A Comparative Study of" Google Translate" Translations: An Error Analysis of English-to-Persian and Persian-to-English Translations. English Language Teaching, 9(3), 13-17.
Google. (n.d.). Google. https://bard.google.com/?hl=in
Hasyim, M., Saleh, F., Yusuf, R., & Abbas, A. (2021). Artificial Intelligence: Machine Translation Accuracy in translating French-Indonesian culinary texts. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3816594
Irfan, M. (2017). Machine Translation. Retrieved from https://www.researchgate.net/publication/320730405
Kadaoui, K., Magdy, S. M., Waheed, A., Khondaker, M. T. I., El-Shangiti, A. O., Nagoudi, E. M. B., & Abdul-Mageed, M. (2023). TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties. arXiv preprint arXiv:2308.03051.
Li, H., Graesser, A. C., & Cai, Z. (2014, May). Comparison of Google translation with human translation. In the twenty-seventh international flairs conference.
Maxfield, M. G., & Babbie, E. R. (2014). Research methods for criminal justice and criminology. Cengage Learning.
McDonald, S. V. (2020). Accuracy, readability, and acceptability in translation. Applied Translation. https://doi.org/10.51708/apptrans.v14n2.1238
Medvedev, Gennady. (2016). Google Translate in Teaching English. Journal of Teaching English for Specific and Academic Purposes, 4.1 (2016), 181–93
Mobaraki, M., & Aminzadeh, S. (2012). A study on different translation evaluation strategies to introduce an eclectic method. International Journal of English Linguistics, 2(6). https://doi.org/10.5539/ijel.v2n6p63
Munday, J. (2016). Introducing translation studies: theories and applications (4th ed.). London and New York: Routledge.
Munthe, I. B., Sipayung, K., & Lestari, F. D. (2023). Comparing The Translation Accuracy Between Google Translate and Professional Translator. Innovative: Journal Of Social Science Research, 3(6), 890-903.
Napitupulu, S. (2017). Analyzing Indonesian-English Abstracts Translation In View of Translation Errors By Google Translate. International Journal of English Language and Linguistics Research, 5, 15-23. European Center for Research Training and Development UK.
Peris, Á., Domingo, M., & Casacuberta, F. (2017). Interactive neural machine translation. Computer Speech & Language, 45, 201-220.
Sanusi, A. (2019). The quality translation analysis of student Qirāah text. Arabi: Journal of Arabic Studies, 4(1), 11. https://doi.org/10.24865/ajas.v4i1.119
Sari, A. N., & Zamzani, Z. (2020). An analysis of translation strategies of honorific term in the film “The boss baby.” Indonesian Journal of EFL and Linguistics, 5(2), 355. https://doi.org/10.21462/ijefl.v5i2.289
Sasmi, A.C., Baharuddin, Wardana, L.A. (2023). Google Nmt And Yandex Nmt Differences in Clarity and Naturalness Of Translating English Text Into Indonesian: A Comparative Study on Machine Translations (Doctoral dissertation, Universitas Mataram).
Schiaffino, R., & Zearo, F. (2005, November). Translation quality measurement in practice. In Proceedings of the 46th Annual Conference of the American Translation Association.
Siad, S. M. (2023). The Promise and Perils of Google's Bard for Scientific Research. HASTAC. Humanities Commons.
Snover, M., Dorr, B., Schwartz, R., Micciulla, L., & Makhoul, J. (2006). A Study of Translation Edit Rate with Targeted Human Annotation. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers (pp. 223–231). Cambridge, Massachusetts, USA: Association for Machine Translation in the Americas.
Su, J., Zhang, X., Lin, Q., Qin, Y., Yao, J., & Liu, Y. (2019). Exploiting reverse target-side contexts for neural machine translation via asynchronous bidirectional decoding. Artificial Intelligence, 277, 103168.
Sugiyono, D. (2013). Metode penelitian pendidikan pendekatan kuantitatif, kualitatif dan R&D.
Sumiati, Baharuddin, & Saputra, A. (2022). The analysis of Google Translate Accuracy in translating procedural and narrative text. Journal of English Education Forum (JEEF), 2(1), 7–11. https://doi.org/10.29303/j.v2i1.270
Tanjung, Sufriati. (2018). Penialain Penerjemahan Jerman-Indonesia. Yogyakarta: Kanwa Publisher
UIN Sunan Kalijaga. (n.d.). Adabiyyat. E-Journal UIN Sunan Kalijaga Yogyakarta. https://ejournal.uin-suka.ac.id/adab/Adabiyyat
Vanjani, M., & Aiken, M. (2020). A comparison of free online machine language translators. J. Manag. Sci. Bus. Intell, 5, 26-31.
Wardana, L. A., Baharuddin, B., & Nurtaat, L. (2022). Kemampuan Mahasiswa melakukan post-editing terhadap Hasil Terjemahan Machine Translation. Jurnal Ilmiah Profesi Pendidikan, 7(1), 53-61.
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.
Published
2024-01-23
How to Cite
Rosita, Baharuddin, Putera, L. J., & Sujana, I. M. (2024). A COMPARATIVE ANALYSIS OF ACCURACY BETWEEN GOOGLE TRANSLATE AND BARD IN TRANSLATING ABSTRACTS OF SCIENTIFIC JOURNALS . Didaktik : Jurnal Ilmiah PGSD STKIP Subang, 10(1), 35 - 44. https://doi.org/10.36989/didaktik.v10i1.2558
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