Investigating Covert and Overt Errors Using Machine Translation according to House’s (2015) TQA Model within Academic Context

الموضوعات : نشریه زبان و ترجمه

Mohammad Iman Askari ¹ , Adnan Satariyan ² , Mahsa Ranjbar ³

1 - Assistant Professor, English Department, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Director, Standardization and Quality Assurance Department, UAE Branch, Islamic Azad University, Dubai, United Arab Emirates
3 - PhD Candidate, English Department, Faculty of Persian Literature and Foreign Languages, Allameh Tabataba’i University, Tehran, Iran

تاريخ الإرسال : 15 الأحد , ذو الحجة, 1442 تاريخ التأكيد : 15 الأحد , ذو الحجة, 1442 تاريخ الإصدار : 21 الخميس , ذو القعدة, 1442

الکلمات المفتاحية: Text, errors, Google Machine Translate (GMT), Translation Quality Assessment (TQA),

ملخص المقالة :

The current study investigated Persian-English translations conducted by a human translator and a machine translator. The researchers employed House’s Translation Quality Assessment (TQA) model to evaluate the differences between the two translated works. Accordingly, they had the Persian texts translated by a human translator and Google Machine Translator (GMT). The translation quality, error recognition, and mismatches of the two translations were subsequently analyzed. The results showed a one-to-one match between the source and target texts regarding the human translator’s work. Furthermore, the results revealed both overt and covert errors when comparing the human and machine translators. The error analysis results also suggested that the quality of the output provided by the GMT can cause misunderstanding in the meaning. Academic texts could mean different in various contexts. Hence, it is necessary to consider human interferences when dealing with the genre of the academic text.

المصادر:

Halliday, M. A. K. (1994). An Introduction to Functional Grammar (Second Ed.). London: Edward Arnold.

Helft, M. (2010). Google’s computing power refines translation tool. The New York Times. Retrieved from http://www.nytimes.com/2010/03/09/technology/09tr anslate.html.

House, J. (1997). Translation Quality Assessment: A Model Re-visited. Tübingen: Narr.

House, J. (2001). Translation Quality Assessment: Linguistic Description versus Social Evaluation. Meta: Translators’ Journal, 46(2), 243-257.

House, J. (2006). Text and context in translation. Journal of Pragmatics, 38(3), 338- 358.

House, J. (2015). Translation Quality Assessment: Past and Present. New York: Routledge.

House, J. (2016). Translation as Communication across Language and Cultures.  New York. Routledge.

Schulz, T. (2013). Translate this: Google’s quest to end the language barrier. Der Spiegel. Retrieved from http://www.spiegel.de/international/europe/google- translate-hasambitious- goals-for-machine-translation-a-921646.html.

Munday, J. (2001). Introducing translation studies: theories and applications. London, Routledge.

Munday, J. (2008). Introducing Translation Studies, Theories and Applications. London & New York: Routledge Tylor and Francis group.

Munday, Jeremy. (2009). Introducing Translation Studies. Abingdon, Oxon: Routledge.

Munday, J. (2016). Introducing Translation Studies: Theories and Applications (4^th ed). London & New York: Routledge.

Scriven, M. (2007). Key Evaluation Checklists. Retrieved from www.wmich.edu/evalctr/checklists/