Abstract
The present paper describes a machine translation (MT) course taught to undergraduate students in the Department of English Language and Literature at Dhofar University in Oman. The course is one of the major requirements for BA in Translation. Fifteen EFL translation students who were in their third year of study were enrolled in the course. The author presents both the theoretical and practical parts of the course. In the theoretical part, the topics covered in the course are outlined. As for the practical part, it focuses on the translation students’ post-editing of online MT output. This is beneficial to the students as free online MT systems can potentially be used as a means for improving student translators’ training and EFL learning. This is achieved through subjecting MT output to analysis or post-editing by the students so that they can focus on the differences between the source and target languages. With this goal in mind, assignments were given to the students to post-edit the Arabic and English MT output of three free online MT systems (Systran, Babylon and Google Translate), discuss the linguistic problems that they spot for each system and choose the one that has the fewest number of errors. The results show that the students, with varying degrees of success, have managed to identify some linguistic errors with the MT output for each MT system and thus produced a better human translation. The paper concludes that there is a need to incorporate MT courses in translation departments in the Arab world, as integrating technology into translation curricula will have great effect on student translators’ training for their future career as professional translators.
Highlights
Machine Translation (MT), which refers to the attempt to automate the process of translating text or speech from one language to another (Arnold et al, 1994), has become a main technology in the current age of information technology
This is beneficial to the students as free online machine translation (MT) systems can potentially be used as a means for improving student translators’ training and EFL learning. This is achieved through subjecting MT output to analysis or post-editing by the students so that they can focus on the differences between the source and target languages. With this goal in mind, assignments were given to the students to post-edit the Arabic and English MT output of three free online MT systems (Systran, Babylon and Google Translate), discuss the linguistic problems that they spot for each system and choose the one that has the fewest number of errors
The results show that the students, with varying degrees of success, have managed to identify some linguistic errors with the MT output for each MT system and produced a better human translation
Summary
Machine Translation (MT), which refers to the attempt to automate the process of translating text or speech from one language to another (Arnold et al, 1994), has become a main technology in the current age of information technology. Due to the important role that MT plays in the translation profession, many universities throughout the world have introduced MT as one of the main courses for both postgraduate and undergraduate students majoring in translation. The author of the current paper taught this course to translation major students in the spring semester of the academic year 2018–2019. During the course students were introduced to the MT technology, with a focus on different MT-related topics such as historical background, main approaches (rule-based vs statistical), tools for language processing, linguistic challenges for Arabic MT and post-editing and evaluation of MT output
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