ABSTRACT

Despite its importance in a globalized world, indirect translation is a peripheral and under-researched topic in translation studies. Existing research on indirect translation is almost exclusively limited to literary translation and focuses mainly on historical aspects. From a methodological perspective, textual analysis based on close reading is the main source of insight into indirect translation, while distant reading using computational approaches remains unexplored. In order to promote methodological innovation, this study gives a replicable demonstration of how to apply supervised machine learning to corpora of indirect translations. The study is based on comparable corpora of proceedings from the European Parliament. Open-access data is used to ensure the replicability of the proposed methodology. Based on the computational findings, the methodological caveats of this approach are discussed.

摘要

尽管间接翻译在全球化世界中很重要，但它在翻译研究中仍是一个外围且研究不足的主题。现有的间接翻译研究几乎完全局限于文学翻译，主要集中在历史方面。从方法论的角度来看，基于细读的文本分析是洞察间接翻译的主要来源，而使用计算方法的远距离阅读仍有待探索。为了促进方法论创新，本研究对如何将监督机器学习应用于间接翻译语料库进行了可复制的演示。该研究基于欧洲议会的可比诉讼程序集。开放获取数据用于确保所提议方法的可复制性。根据计算结果，