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Postediting machine translation output: subject-matter experts versus professional translators

机译：Postiting机器翻译输出：主题专家与专业翻译

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摘要

This study compares the quality of postediting performed by subject-matter experts as opposed to professional translators. A total of 10 professional translators and 10 engineers postedited a 482-word technical text pre-translated from English into Turkish using data-based machine translation system, Google Translate. The findings suggest that, for this particular task (technical translation), translators' and engineers' postediting quality is similar as far as the categories of mistranslation, accuracy, and consistency are concerned. Engineers performed significantly better than translators only in the terminology category. In the language category, translators made significantly fewer (minor) errors than engineers. The qualitative data analysis revealed that, for this particular task, a degree in translation does not directly correlate with postediting quality, unless it is combined with subject-matter knowledge and professional experience in translation. Finally, the present study indicates that - both for the engineers and the professional translators - expertise and experience in the subject matter are important factors determining postediting quality.
机译：这项研究比较了主题专家与专业翻译人员进行的发布质量。总共有10名专业翻译人员和10名工程师使用基于数据的机器翻译系统Google Translate发布了482个单词的技术文本，将其从英语预翻译成土耳其语。调查结果表明，就误译，准确性和一致性的类别而言，对于此特定任务（技术翻译），翻译人员和工程师的张贴质量是相似的。仅在术语类别上，工程师的表现明显优于翻译。在语言类别中，翻译员犯的（次要）错误比工程师少得多。定性数据分析显示，对于此特定任务，翻译学位不会与发布的质量直接相关，除非将其与主题知识和翻译专业经验相结合。最后，本研究表明-对于工程师和专业翻译人员-主题方面的专业知识和经验是决定邮寄质量的重要因素。

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