Translation Shifts on Reference by Machine Translation in Descriptive Text

Keywords: descriptive text, machine translation, reference, shifts, translation


Translation shifts are one of strategy to get a high-quality translation. It’s also used to solve the absent meaning on the target text. The objectives of this research are to describe the translation shifts (based on the theory of Blum-Kulka about kinds of shift and Halliday and Matthiesen on cohesion theory), which are done by machine translation in descriptive texts. The researcher used a descriptive qualitative research design to achieve the aims of this research. The source of data in this research is descriptive text. The data of this research are pair of words in source and target text. The form of words (pair of words in source and target) are in reference form based on the theory of Halliday about lexical devices. The researcher used interactive data analysis (data condensation, data display, and verifying/conclusion) to get the research findings. This research shows that Yandex translation made translation shifts more (35 times) often than the others. From the whole types of translation shifts (cohesion shifts: implicitation, explicitation, and meaning change), implicitation shift placed a high frequency among machines translation, however explicitation shift placed in the low frequency, and the medium frequency is placed by meaning change. It is to indicate that machine translation still lacks to produce a high level in the target than a source.      

Author Biography

Kammer Tuahman Sipayung, University of HKBP Nommensen
English Language Department


Ahangar, A. A., & Rahnemoon, S. N. (2019). The level of explicitation of reference in the translation of medical texts from English into Persian: A case study on basic histology. Lingua, 228(46).
Bahaziq, A. (2016). Cohesive Devices in Written Discourse: A Discourse Analysis of a Student’s Essay Writing. English Language Teaching, 9(7), 112.
Bloor, M. (2017). Systemic functional linguistics. The Routledge Handbook of Critical Discourse Studies.
Bogdan, B., & Bilken, S. K. (2007). Quality Research for Education: An Introduction to Theory and Methods. Boston : Allyn and Bacon.
Costa-jussa, M. R. (2015). Towards human linguistic machine translation evaluation, Digital Scholarship in the Humanities, 30(2), June 2015, Pages 157–166
Dhakar, B. S., Sinha, S. K., & Pandey, K. K. (2013). A Survey of Translation Quality of English to Hindi Online Translation Systems (Google and Bing). International Journal of Scientific and Research Publications, 3(1), 2250–3153.
Fitri, M., Lia, D., Indrayani, M., & Citraresmana, E. (2014). The Equivalence and Shift in the Indonesian Translation of English Adjective Phrases, Research on Humanities and Social Sciences 4(11), 109–114.
Gerot, & Wignel. (n.d.). Making Sense of Functional Grammar. Gerdstabler. Sydney: Antipodean.
Halliday, M. A. K. (2014). Halliday’ s Introduction to Functional Grammar. London and Newyork: Routledge Taylor & Franscis Group.
Harper, K. E. (2018). Machine translation. Soviet and East European Linguistics, (October), 133–142.
Julita, P. (2013). Shift of Cohesion and Coherence in Translation of the Short Second Life of Bree Tanner into Kisah Singkat Bree Tanner. HUMANIS. 5(2) 1-8
Károly, K. (2014). Referential cohesion and news content. Target. International Journal of Translation StudiesTarget / International Journal of Translation StudiesTarget, 26(3), 406–431.
Karoly, K., Ábrányi, H., Deák, S., Laszkács, Á., Mészáros, A., & Seresi, M. (2013). Cohesion and news translation. Acta Linguistica Hungarica, 60(4), 365–407.
Lawrence Venuti. (2012). The Translation Studies Reader. (M. Baker, Ed.), The Translation Studies Reader. London and Newyork: Taylor & Francis Group.
Noviarini, T. (2021). The Translation Results of Google Translate, SMART, 7(1), 21–26.
Machali, R. (2000). Pedoman Bagi Penerjemah. Jakarta: PT Grasindo.
Meyer, T., & Webber, B. (2013). Implicitation of Discourse Connectives in (Machine) Translation. Proceedings of the Workshop on Discourse in Machine Translation (DiscoMT), 12(2), 19–26.
Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative Data Analysis. USA: SAGE Publication Ltd.
Noor, R., Sinar, T. S., Ibrahim-bell, Z., & Setia, E. (2017). Metafunctional Shifts in the Translation of Student and Professional Translators. International Journal of Sciences: Basic and Applied Research (IJSBAR), 4531(ii), 85–101.
Parazaran, S., & Motahari, S. M. (2015). Investigating Grammatical Cohesive Devices : Shifts of cohesion in translating narrative text type. International Journal of Foreign Language Teaching & Research, 3(10), 63–82.
Sipayung, K. T. (2018). The Impact of Translation Shift and Method on Translation Accuracy Found at Bilingual History Textbook. Jurnal Humaniora, 30(1), 58.
Sipayung, K. T., Lubis, S., Setia, E., & Silalahi, R. (2017). Explicitation and Implicitation of Conjuctive Relation in Target Text of Principle Language Learning and Teaching(PLLT). IJELTAL (Indonesian Journal of English Language Teaching and Applied Linguistics), 2(1), 83–93.
Stevanović, I., & Radičević, L. (2012). Comparative Analysis of Machine Translation Systems. International Journal of Computer Applications, 12(2), 5–8.
Tohmetov, Ushakov, & Vanushin. (2014). The Problems of Machine Translation Study Case : English – Arabic. In Молодежь и Современные Информационные Технологии: Сборник Трудов XII Всероссийской Научно-Практической Конференции Студентов, Аспирантов и Молодых Ученых, г. Томск, 12-14 Ноября 2014 г. Т. 2.—Томск,Vol. 2 No, 267–268.
Widarwati, N. T. (2015). An Analysis of Rank-Shift of Compound Complex Sentence Translation, Journal of Education and Practice, 6(30), 126–135.
Wu, J. (2014). Shifts of Cohesive Devices in English-Chinese Translation. Theory and Practice in Language Studies, 4(8), 1659–1664.
How to Cite
Sipayung, K. (2021). Translation Shifts on Reference by Machine Translation in Descriptive Text. Indonesian Journal of EFL and Linguistics, 6(1), 235-248.