Translating science fiction in a CAT tool: machine translation and segmentation settings

Translating science fiction in a CAT tool: machine translation and segmentation settings
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DOI:
10.12807/ti.115201.2023.a11
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发表时间:
2023-02
期刊:
The International Journal of Translation and Interpreting Research
影响因子:
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通讯作者:
Lucas Nunes Vieira;Natalie Zelenka;Roy Youdale;Xiaochun Zhang;M. Carl
Lucas Nunes Vieira;Natalie Zelenka;Roy Youdale;Xiaochun Zhang;M. Carl
中科院分区:
其他
文献类型:
--
作者:
Lucas Nunes Vieira;Natalie Zelenka;Roy Youdale;Xiaochun Zhang;M. Carl

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人们对机器辅助文学翻译的兴趣与日俱增,但关于计算机辅助翻译(CAT)工具和机器翻译(MT)如何在文学翻译中相结合的研究仍处于起步阶段,尤其是对于非欧洲语言。本文介绍了两项在TRADOS工作室进行的英汉翻译使用神经机器翻译科幻短篇小说的探索性研究。其中一项研究比较了编辑后与没有机器翻译的情况。另一种是研究在屏幕上呈现文本以进行发布编辑的两种方式,即通过将文本分段为段落或句子。我们使用Trados Studio的Qualititivity插件收集了数据,并描述了一种通过翻译与翻译技术研究中心(CRITT)的翻译过程研究数据库来分析使用该插件收集的数据的方法。虽然后期编辑需要较少的技术工作,但我们并没有发现机器翻译明显节省了时间。平均而言,段落切分与较少的后期编辑工作有关,尽管与翻译人员的高度可变性有关。我们从现状偏见等更广泛的概念来讨论结果,并呼吁对机器翻译帮助文学翻译的不同方式进行更多的研究,包括将其用于比较目的,或如一位参与者所说的,用于启发。
There is increasing interest in machine assistance for literary translation, but research on how computer-assisted translation (CAT) tools and machine translation (MT) combine in the translation of literature is still incipient, especially for non-European languages. This article presents two exploratory studies where English-to-Chinese translators used neural MT to translate science fiction short stories in Trados Studio. One of the studies compares post-editing with a ‘no MT’ condition. The other examines two ways of presenting the texts on screen for postediting, namely by segmenting them into paragraphs or into sentences. We collected the data with the Qualititivity plugin for Trados Studio and describe a method for analysing data collected with this plugin through the translation process research database of the Center for Research in Translation and Translation Technology (CRITT). While post-editing required less technical effort, we did not find MT to be appreciably timesaving. Paragraph segmentation was associated with less postediting effort on average, though with high translator variability. We discuss the results in the light of broader concepts, such as status-quo bias, and call for more research on the different ways in which MT may assist literary translation, including its use for comparison purposes or, as mentioned by a participant, for ‘inspiration’.