Online Machine Translation Efficiency in Translating Fixed Expressions Between English and Arabic (Proverbs as a Case-in-Point)
DOI:
https://doi.org/10.17507/tpls.1305.07Keywords:
machine translation, fixed expressions, proverbs, translation methods, Google translateAbstract
Doubtless, Machine Translation has affected translation as a process and a product. This study tests MT's effectiveness in translating proverbs between English and Arabic. It investigates one important CAT tool device. It aims to attest which MT will be more communicative, semantic or literal giving target equivalent and clarifying the error type the MT would make. To achieve these aims, thirty proverbs, half Arabic and half English, have been randomly selected, taken from The Dictionary of Common English Proverbs Translated and Explained written by Attia (2004) and then translated using five different online MTs: Google, Reverso, Yandex, Systran, and Bing. As Alabbasi (2015) suggested, the researcher adopted Newmark's (1988) Taxonomy of translation methods, selecting three major divisions that include the other types in one way or another viz. Literal, Semantic and Communicative. Analyzing data, Kruskal-Wallis Test and Chi-square were used as well as descriptive statistics. It is found that the most translation method MT produced when faced with a proverb is the literal, semantic and communicative respectively. Bing is the most effective MT providing communicative proverbial equivalents. Bing and Google, in the same rank, provide semantic equivalents. Furthermore, the least effective MT among the five is Yandex. MT errors diverge between missing the implied meaning, weakly structured translations, wrong synonyms and meaning distorting.
References
Abdulhaq, S. (2016). Machine Translation: Limits of Accuracy and Fidelity. An MA thesis. An-Najah National University, Nablus, Palestine.
Acikgoz, F., & Sert, O. (2006). Interlingual Machine Translation: Prospects and Setbacks. Online Submission, 10(3), 1-16.
Alabbasi, A. (2015). Introduction to Translation: A Theoretical and Practical Book 4th ed. Sana’a: Al-Ameen Publishing and Distribution.
Ali, M. (2020). Quality and Machine Translation: An Evaluation of Online Machine Translation of English into Arabic Texts. Open Journal of Modern Linguistics, 10, 524-548. DOI: 10.4236/ojml.2020.105030.
Al-Kabi, M., Gigieh, A., Alsmadi, I., Wahsheh, H., & Haidar, M. (2013). An opinion analysis tool for colloquial and standard Arabic. In The Fourth International Conference on Information and Communication Systems (ICICS 2013) (pp. 23-25).
Al-khresheh, M. H., & Almaaytah, S. A. (2018). English proverbs into Arabic through machine translation. International Journal of Applied Linguistics and English Literature, 7(5), 158-166.
Almahasees, Z., & Mahmoud, S. (2022). Evaluation of Google Image Translate in Rendering Arabic Signage into English. World Journal of English Language, 12(1), 185-197.
Alshammari, J. N. (2015). Examining Nida's translation theory in tendering Arabic proverbs into English: A comparative analysis study. International Journal of English Language and Linguistics Research, 3(8), 45-57.
Anderson, D. D. (1995). Machine Translation as a Tool in Second Language Learning. CALICO Journal, 13, 68-96.
As-Safi, A. B. (2002). Translation Theories, Strategies and Basic Theoretical Issues. Petra University. Retrieved From: http://www.uop.edu.jo/download/research/members/424_2061_A.B.pdf. On 17/12/2021
Attia, M. (2004). The Dictionary of Common English Proverbs Translated and Explained. http://www.attiaspace.com/Publications/CommonProverbs.pdf. On 16/10/2021.
Baker, M. (1992). In Other Words, London & New York: Routledge.
Balkan, L. (1992) Translation Tools. Meta, 27(30), 408-20
Barbour, F. M. (1963). Some uncommon sources of proverbs. Midwest Folklore, 13(2), 97-100.
Belam, J. (2003). Buying up to falling down. In Workshop on Teaching Translation Technologies and Tools. From: https://aclanthology.org/2003.mtsummit-tttt.1.pdf on 15/10/2022
Birla, V. K., Ahmed, M. N., & Shukla, V. N. (2009). Multiword expression extraction—text processing. Proceedings of ASCNT-2009, CDAC, Noida, India, 72-77.
Champollion, Y. (2001). Machine translation (MT), and the future of the translation industry. Translation journal, 5(1). Available on: https://scholar.google.com/scholar?hl=ar&as_sdt=0%2C5&q=Machine+translation+%28MT%29%2C+and+the+future+of+the+translation+industry&btnG=#d=gs_cit&t=1660262011911&u=%2Fscholar%3Fq%3Dinfo%3At3x6wX5qm4UJ%3Ascholar.google.com%2F%26output%3Dcite%26scirp%3D0%26hl%3Dar on 20/10/2022.
Costa, Â., Ling, W., Luís, T., Correia, R., & Coheur, L. (2015). A linguistically motivated taxonomy for Machine Translation error analysis. Machine Translation, 29(2), 127-161. https://doi.org/10.1007/s10590-015-9169-0
Ghazala, H. (1995). Translation as Problems and Solutions: A Coursebook for University Students and Trainee Translators. Beirut: Dar wa Maktabat Al-Hilal.
Ghazala, H. (1995). Translation as Problems and Solutions: A course-book for university students and trainee translators (7th ed). Beirut: Dar wa Maktabat AL-Hilal.
Hamdi. S., Nakae. K., & Okashs, M. (2013). Online Translation of Proverbs between Availability and Accuracy-ISLLLE, Japan,
Ismajli, V. & Maliqi, F. (2021). The effectiveness and efficiency of human translation versus machine translation Valentina in 1st Alumni Research Conference 2021 (pp. 307-327). Kolegi AAB, Department of English.
Jabak, O. (2019). Assessment of Arabic-English translation produced by Google translate. International Journal of Linguistics, Literature and Translation (IJLLT) ISSN, V. 2, I. 4, pp. 238-274.
Latief, M. R. A., Saleh, N. J., & Pammu, A. (2020). The effectiveness of machine translation to improve the system of translating language on cultural context. In IOP Conference Series: Earth and Environmental Science (Vol. 575, No. 1, p. 012178). IOP Publishing.
Lembersky, G., Ordan, N., & Wintner, S. (2012). Language models for machine translation: Original vs. translated texts. Computational Linguistics, 38(4), 799-825.
León Bergasa, A., & Lorés Sanz, R. (2019). A contrastive study of errors in automatic translation and human translation in tourist texts: an evaluation of Google Translator, Systran and Bing. Available at https://zaguan.unizar.es/record/85369?ln=fr on 17/12/2021.
Li, H., Graesser, A. C., & Cai, Z. (2014). Comparison of Google translation with human translation. In The Twenty-Seventh International Flairs Conference.
Lin, G. H. C., & Chien, P. S. C. (2009). Machine Translation for Academic Purposes. Proceedings of the International Conference on TESOL and Translation 2009, December 2009, pp.133-148
Mieder, W. (1994). Proverbs are never out of season: Popular wisdom in the modern age. Oxford University Press, USA.
Newmark, P. (1988). A Textbook of Translation. Prentice Hall: China
Newmark, P. (1988). Pragmatic translation and literalism. TTR: traduction, terminologie, rédaction, 1(2), 133-145.
Nida, E. A., & Taber, C. R. (1982). The theory and practice of translation (Vol. 8). Brill Archive.
Oxford Reference, Science and Technology, from: https://www.oxfordreference.com/page/scienceandtech/science-and-technology on 15/12/2022.
Polat, Y., Zakirov, A., Bajak, S., Mamatzhanova, Z., & Bishkek, K. (2018). Machine Translation for Kyrgyz Proverbs—Google Translate Vs. Yandex Translate-From Kyrgyz into English and Turkish. In Сборник содержит материалы Шестой Международной конференции по компьютерной обработке тюркских языков «TurkLang-2018»(Ташкент, Узбекистан, 18–20 октября 2018 г.) Данная публикация предназначена для научных работников, преподавателей, аспирантов и студентов, специализирующихся в области.
Sakre, M. M. (2019). Machine translation status and its effect on business. Journal of the ACS, 10. From: https://scholar.google.com/scholar?hl=ar&as_sdt=0%2C5&q=Machine+translation+status+and+its+effect+on+business.+Journal+of+the+ACS%2C+10.%E2%80%8F+&btnG= on 20/12/2021.
Sharma, M., & Goyal, V. (2011). Extracting proverbs in machine translation from Hindi to Punjabi using relational data approach. International Journal of Computer Science and Communication, 2(2), 611-613.
Sofer, M. (2006). The translator's handbook. Schreiber Pub. Systran: Past and Present.
Thriveni, C. (2002). Cultural elements in translation: The Indian perspective. Available online: https://translationjournal.net/journal/19culture.htm retrieved on 10/7/2022.
Vauquois, B. (1968). A survey of formal grammars and algorithms for recognition and transformation in mechanical translation. In J.H. Morrell (Ed.), Proceedings of the International Federation for Information Processing Congress (IFIP-68), (Vol. 2, pp. 1114–1122).
Venuti, L. (Ed.). (1998). Strategies of Translation. In Baker, M. (ed.) The Routledge Encyclopedia of Translation Studies. London: Routledge, 240-244.
Vilar, D., Xu, J., d’Haro, L. F., & Ney, H. (2006). Error analysis of statistical machine translation output. In Proceedings of the fifth international conference on language resources and evaluation (LREC’06).
Vinay, J-P., & Darbelnet, J. (1958). Comparative Stylistics of French and English: a Methodology for Translation, translated by J. C. Sager and M. J. Hamel, Amsterdam/ Philadelphia: John Benjamins.
