INSTAGRAM TRANSLATE AND HUMAN TRANSLATION IN THE ENGLISH CAPTIONS OF JOKOWI’S ACCOUNT: AN ANALYSIS OF KOPONEN’S ERROR CATEGORY

Amazia Trifena Putri(1*), Harris Hermansyah Setiajid(2)


(1) Universitas Sanata Dharma
(2) Universitas Sanata Dharma
(*) Corresponding Author

Abstract


Translation technology has developed so rapidly that it might replace human translation in the near future. Artificial intelligence-based translation machines increasingly resemble humans in doing translation jobs. Instagram Translate (IG Translate), for example, has shown a growing improvement in translating photo captions posted by users. Many studies have been carried out to look into IG Translate performance in various language pairs. In 2016 Instagram started providing a translation feature for its users to translate the photo captions posted by users. There is a possibility that the translations might contain errors, which are worth studying to measure the IG Translate translation performance. This study seeks to investigate Koponen’s translation errors category done by IG Translate in translating the photo captions in Jokowi's official Instagram account. The questions remain, however, whether the IG Translate performs better than a professional human translator. This research is designed to measure the translation performance by IG Translate and human translator by finding the errors possibly and to analyze the translation strategies applied by the machine and the human. The translation error analysis is expected to see the translation strategies are to find out whether the machine and the human apply different or the same strategies. The sample of the photo captions used for the analysis is from Jokowi's official Instagram account starting from March 2020 to September 2020. This range is chosen because it represents the beginning of the Covid-19 pandemic and the way the government in the process of overcoming the pandemic. The research is expected to give a theoretical benefit by enriching translation research repertoire as well as a practical benefit for IG Translate developer to improve its algorithm and for social media users to input their photo captions in a way that can be translated well by the machine.


Keywords


Translation Performance, Koponen, IG Translate, Human Translation, Machine Translation

Full Text:

PDF

References


Arnold, Douglas, Lorna Balkan, Siety Meijer, R. Lee Humphreys and Louisa Sadler. Machine Translation: an Introductory Guide. Oxford: NCC Blackwell Ltd., 1994.

Hutchins, John. Commercial Systems: The State of the Art. 2003. Computers and Translation: a Translator’s Guide. ed. Somers, Harold. Philadelphia: John Benjamins Publishing Company, 2003: pp.161-174.

Hutchins, John and Harold Somers. An Introduction to Machine Translation. London: Academic Press Limited, 1992.

Koponen, Maarit. “Assessing Machine Translation Quality with Error Analysis” in Electronic Proceedings of the KäTu Symposium on Translation and Interpreting Studies 4. Helsinki: University of Helsinki, 2010.

Kurnianto, Damianus D. “Google Translate Assessment with Error Analysis: An Attempt to Reduce Errors”. Thesis. Yogyakarta: Universitas Sanata Dharma, 2012.

Turovsky, Barak. “Ten Years of Google Translate”. Google Official Blog. 2016. (www.blog.google.com). 22 Sep. 2016


Article Metrics

Abstract view : 733 times
PDF - 316 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 English Language and Literature International Conference (ELLiC) Proceedings

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Electronic ISSN: 2579-7263
CD-ROM ISSN: 2579-7549

Published by

FACULTY OF FOREIGN LANGUAGE AND CULTURE
UNIVERSITAS MUHAMMADIYAH SEMARANG
Jl. Kedungmundu Raya No.18 Semarang, Central Java, Indonesia
Phone: +622476740295, email: ellic@unimus.ac.id