Postediting machine traslation output ad its revision: Subject-matter experts versus professional translators
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- Tez No: 401067
- Danışmanlar: PROF. ANTHONY PYM
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- Üniversite: Unıversıtat Rovıra I Vırgılı
- Enstitü: Yurtdışı Enstitü
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Özet (Çeviri)
The present research aims to explore the specific characteristics of the postediting processes performed by subject-matter experts as opposed to professional translators. We compare the ways engineers and professional translators postedit a technical text, in terms of processing speed, time spent on documentation and the number of changes. We also compare the texts postedited by engineers and professional translators with regard to quality, using LISA QA Model 3.1. Further, we explore which of the following workflows is faster and produces outputs of higher quality: Postediting MT output by engineers and revising the postedited text by professional translators, or vice-versa. We conducted two sets of experiments that were screen-recorded with BB Flashback. First, ten professional translators and ten engineers postedited a 482-word text on the dismantling of end-of-life vehicles; the text had previously been translated by Google Translate. Then they filled out post-assignment questionnaires. Second, each group revised the posteditings performed by the other group. The findings suggest that expertise and experience in the subject-matter are the main factors determining postediting quality. When the recurrent errors are penalized and the outlier participants were removed, the engineers' postediting of technical texts is of significantly higher quality than the translators'. When postediting, the translators' and the engineers' processing speed did not differ significantly. For technical texts, the quality improvement (added value) brought about by engineer-revision of translator-postediting is higher than vice-versa. However, this added value is significant only when the recurrent errors are penalized. Further, the quality of both the postedited texts and their revised versions (either performed by professional translators or engineers) changes significantly as a result of penalizing and unpenalizing recurrent errors. Keywords Postediting, machine translation, professional translators, subject-matter experts, processing speed, translation quality, recurrent errors, technical translations, LISA QA Model 3.1., Google Translate, documentation, self-revision.
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