Using Machine Translation Error Identification to Improve Translation Students’ Post-Editing Skills | ||||
| Transcultural Journal of Humanities and Social Sciences | ||||
| Articles in Press, Accepted Manuscript, Available Online from 08 February 2023 | ||||
| Document Type: Original papers | ||||
| DOI: 10.21608/tjhss.2023.184675.1164 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Nermine Yehia Emara 
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| Badr University in Cairo | ||||
| Abstract | ||||
| Abstract Attempts to investigate challenges facing translation students in post-editing remain limited in literature. This research investigates a common challenge observed during post-editing training using SDL Trados which is deciding whether to post-edit MT output or translate from scratch. Taking such decisions by translation students may need more focused procedures and criteria to improve this decision-making capability. The current research suggests integrating MT error identification proposed by Daems J, Vandepitte S, Hartsuiker RJ and Macken L (2016) as basic criteria in post-editing process and tested its effects on improving their performance in post-editing process regarding decision taking and time consumed. A quasi- experimental approach was adopted, and the experiment was applied on thirty (30) translation students at university level divided into a control group and an experimental group. A pre-test was given to both groups to identify both performance and time consumed in the post-editing process. MT error identification techniques and Statistical MT error types were introduced in a five-day workshop using a task-based approach to instruct the experimental group. The control group received traditional post-editing training with no focus on MT error types. A post-test was administered to both groups to test the improvement in post-editing skills. The findings showed the significant improvement in students’ post-editing skills. This research would contribute to enhancing translation training courses provided to cope with the continuous advancement in translation technologies and market needs. | ||||
| Keywords | ||||
| Machine Translation; Post-editing; Decision making; Error Identification | ||||
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