| Summary: | 碩士 === 國立臺灣科技大學 === 應用外語系 === 104 === Machine translation (MT) has been gone along for over sixty years, and gradually develops a translation combination of Machine Translation (MT) and Post-Editing (PE). Although this combination successfully increases the productivity and quality of translation, some problems, like word sense disambiguation and reordering, derived from MT still make PE efficiency impossible.
In order to solve above MT problems, this study raises up four study questions: (1) what are the major problems that affect the quality of current MT? (2) what are the bottlenecks that compromise the efficiency of post-editing in MAHT? (3) what kinds of training are needed to enable post-editors to address the problems derived from MT’s poor reordering? (4) how can a language parser help with the training to untangle cluttered output texts from MT in post-editing training?
This study uses Google Translate (GT) as the testing model to firstly produce the output out of different sample texts. Then the GT texts were compared with the original texts (OT) parsed with a language parser to identify the errors between GT and OT. Finally, those problems were summarized and, as a result, produce a checklist of 40 checkpoints and 7 guidelines. Moreover, around 19 training goals are laid out for the reference of post-editor training programs.
According to the results, four research questions of this study are answered: (1) the major problems that affect the quality of current MT are WSD and reordering, mainly reordering; (2) the bottlenecks that compromise the efficiency of post-editing in MAHT is reordering; (3) instilling and enhancing post-editors’ perspective of linguistic are needed to address the problems derived from MT’s poor reordering; (4) the guideline and checkpoints can help the training to untangle cluttered output texts from MT in post-editing training. All in all, with the aid of the checklist, the translators will gradually improve their PE skills, as well as the productivity and quality of translation.
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