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POETIC TRANSLATION AND STUDENTS’ APPRECIATION THROUGH HUMAN TRANSLATOR AND MACHINE SYSTEM
(1) STKIP Kusuma Negara, Indonesia
(2) Sanata Dharma University, Indonesia
(3) Muhammadiyah Palangkaraya University, Indonesia
(4) Satya Wacana Christian University, Indonesia
(5) STKIP Kusuma Negara, Indonesia
(*) Corresponding Author
Abstract
The engagement with poetry is a personalized journey that transcends standardized methodologies. Key to this process is complete immersion in the poetic experience, alongside evaluators’ openness to both human and machine-generated translations from Indonesian to English. The overarching goal is to enhance students’ discernment and appreciation of these translated works. The study’s specific objectives involved comparing poetic translation assessments by evaluators for both human translators and machine systems. It was to assess students’ appreciation of poetry through the lens of both translation methods across three different institutions. The research employed a mixed-methods approach, combining quantitative and qualitative descriptive analyses, including descriptive statistics. The dataset comprised two Indonesian poems by Taufik Ismail, rated using a score as proposed by Nababan. Findings indicate that human translators outperformed machine systems in terms of accuracy, acceptance, and readability. While students from Institutions 1 and 2 preferred human-translated poetry, students from Institution 3 favoured machine-translated versions. This suggests that human translation quality remains superior.
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Adiel, M. A. E., Elsadig, M. A., Altigani, A., Mohamed, Y. A., Ahmed, B. E. S., & Elhassan, S. M. O. (2023). Accuracy and problems of machine-based translation in contrast to human-based translation when rendering health awareness texts versus poetry texts. Academic Journal of Interdisciplinary Studies, 12(4), 223–231. https://doi.org/10.36941/ajis-2023-0108
Amirrudin, M., Nasution, K., & Supahar, S. (2020). Effect of variability on Cronbach alpha reliability in research practice. Jurnal Matematika, Statistika dan Komputasi, 17(2), 223–230. https://doi.org/10.20956/jmsk.v17i2.11655
Anggriawan, E., Farid, F., & Sari, R. F. (2023). Sentences similarity detection in Indonesian poetry comparison using Siamese malstm. ICIC Express Letters, 17(4), 389–396. https://doi.org/10.24507/icicel.17.04.389
Banik, D., Ekbal, A., Bhattacharyya, P., Bhattacharyya, S., & Platos, J. (2019). Statistical-based system combination approach to gain advantages over different machine translation systems. Heliyon, 5(9), 1-9. https://doi.org/ 10.1016/j.heliyon.2019.e02504
Casquilho, M., & Buescu, J. (2022). Standard deviation estimation from sums of unequal-size samples. Monte Carlo Methods and Applications, 28(3), 235–253. https://doi.org/10.1515/mcma-2022-2118
Dawah, W. A. A.-S. (2024). The human translation and the electronic translation, an applied comparative study of selected Hebrew poetic texts. Journal of Language Studies, 8(5), 58–83. https://doi.org/10.25130/Lang.8.5.4
Dunder, I., Seljan, S., & Pavlovski, M. (2021). What makes machine-translated poetry look bad? A human error classification analysis. Central European Conference on Information and Intelligent Systems, 183–191.
Faulkner, S. L. (2019). Poetic inquiry: Craft, method, and practice. Oxfordshire: Routledge.
Finnegan, R. (2018). Oral poetry: Its nature, significance, and social context. Oregon: Wipf and Stock Publishers.
Glesne, C. (2016). Becoming qualitative researchers: An introduction. Washington: Eric.
Gönen, S. İ. K. (2018). Implementing poetry in the language class: A poetry-teaching framework for prospective English language teachers. Advances in Language and Literary Studies, 9(5), 28–42. https://doi.org/10.7575/aiac.alls.v.9n.5p.28
Heilmann, A. (2020). Profiling effects of syntactic complexity in translation: A multi-method approach (Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen).
Hennink, M., Hutter, I., & Bailey, A. (2020). Qualitative research methods. Melbourne: Sage.
Hidayat, A., Muliastuti, L., & Dewanti, R. (2022). Condition of poetry appreciation teaching materials at Kuningan University. UNISET 2021: Proceedings of the 2nd Universitas Kuningan International Conference on System, Engineering, and Technology,1-9. http://dx.doi.org/10.4108/eai.2-12-2021.2320228
Houache, A., & Zedek, H. (2023). A stylistics study of the linguistic deviations in Emmett Williams’ selected poems: She loves me, do you remember’and’ the moon is green’ (Dissertation Université IBN Khaldoun-Tiaret).
Khan, H., Ali, W., & Naeem, R. (2023). Stylistic analysis of the poem “Ode to a nightingale” by John Keats. Journal of Namibian Studies: History Politics Culture, 33(3), 5535–5560. https://doi.org/10.59670/jns.v33i.4967
Kim, H., Sefcik, J. S., & Bradway, C. (2017). Characteristics of qualitative descriptive studies: A systematic review. Research in Nursing & Health, 40(1), 23–42. https://doi.org/10.1002/nur.21768
Ma, Y., & Wang, B. (2020). Description and quality assessment of poetry translation: Application of a linguistic model. Contrastive Pragmatics, 3(1), 89–111.
Macken, L., Prou, D., & Tezcan, A. (2020). Quantifying the effect of machine translation in a high-quality human translation production process. Informatics, 7(2), 12. https://doi.org/10.3390/informatics7020012
Mahbub, R., Khan, I. T., Anuva, S. S., Shahriar, M. S., Laskar, M. T. R., & Ahmed, S. (2023). Unveiling the essence of poetry: Introducing a comprehensive dataset and benchmark for poem summarization. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 14878–14886. https://doi.org/10.18653/v1/2023.emnlp-main.920
Melgar Hernández, R. (2022). Neural machine translation as a translation tool: The case study of Spanish at the translation service of the Council of the European Union (Master thesis, National University of Distance Education).
Mulatsih, M. V. E. (2020). Introduction to prose in English language teaching. Yogyakarta: Sanata Dharma University Press.
Nababan, M., Nuraeni, A., Sumardiono. (2012). Pengembangan model penilaian kualitas terjemahan. Kajian Linguistik dan Sastra, 24(1), 39-57.
Ni, J., & Wang, C. (2022). Research on translation of hyperbole based on effects studies‐‐Taking selected poems of Li Bai in library of Chinese classics as an example. International Journal of Social Science and Education Research, 5(5), 411–416. https://doi.org/10.6918/IJOSSER.202205_5(5).0058
Nuryadi, N. (2021). Denotation and connotation in London’s William Blake. Makna: Jurnal Kajian Komunikasi, Bahasa, dan Budaya, 9(2), 48–57. https://doi.org/10.33558/makna.v9i2.2976
Pallavi, K., & Mojibur, R. (2018). A preliminary pragmatic model to evaluate poetry translation. Babel, 64(3), 434–463. https://doi.org/10.1075/babel.00046.pal
Pudjiati, D., & Zuriyati. (2022). Students’ perception of cultural values in “travel” poem through youtube. IJLECR - International Journal of Language Education and Culture Review, 8(1), 41–50. https://doi.org/10.21009/IJLECR.081.06
Qassem, M., & Aldaheri, M. M. (2023). Can machine translate dialogue acts: Evidence from translating dialogues from English to Arabic. 3L: Language, Linguistics, Literature, 29(4), 63-81. https://doi.org/10.17576/3L-2023-2904-05
Rahman, M. S. (2020). The advantages and disadvantages of using qualitative and quantitative approaches and methods in language “testing and assessment” research: A literature review. Journal of Education and Learning 6(1), 102-102. https://doi.org/10/5539/jel.v6n1p102
Rustandi, P. (2020). Connotative and denotative meaning in poem “who am I, without exile?" by Mahmoud Darwish. TEXTURA, 1(2), 30–36.
Sedlanić, R. (2022). Machine translation vs. human translation: Semantic distinctions in English-Croatian translations (Thesis, University of Rijeka, Rijeka, Croatia).
Seljan, S., Dunđer, I., & Pavlovski, M. (2020). Human quality evaluation of machine-translated poetry. 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 1040–1045. https://doi.org/10.23919/MIPRO48935.2020.9245436
Stahlberg, F. (2020). Neural machine translation: A review. Journal of Artificial Intelligence Research, 69, 343–418. https://doi.org/10.1613/jair.1.12007
Stockwell, P. (2019). Cognitive poetics: An introduction. Oxfordshire: Routledge.
Vaske, J. J., Beaman, J., & Sponarski, C. C. (2017). Rethinking internal consistency in Cronbach’s alpha. Leisure Sciences, 39(2), 163–173. https://doi.org/10.1080/01490400.2015.1127189
DOI: https://doi.org/10.24071/llt.v27i2.9299
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