《速度与激情》中非标准英语词汇的翻译技巧

Kresnu Ahda Yudyantama, Arso Setyaji, Rahmawati Sukmaningrum
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引用次数: 0

摘要

本研究考察了《速度与激情:东京漂移》剧本中非标准英语的翻译方法。本研究采用定性方法。在本研究中,研究者评估了《速度与激情:东京漂移》剧本中102个非标准英语单词的翻译技巧。Molina和alir的翻译过程概念被研究者所采用。在本研究中,研究者发现了直译、建立对等、改编、借用、语言压缩、概括、还原、语言放大、特殊化等9种翻译技巧。此外,占主导地位的翻译技术是直译技术,使用了35次,百分比为54,61%,其次是建立等效18次,44%使用了13次,适应7次,15%使用了5次,借用7次,15%从数据中使用了5次,语言压缩3次,57%使用了3次,概括使用了2次,百分比2,减少使用了2次,百分比2,75%,语言放大使用了1次,百分比1,79%。特殊化率为1.79%,使用1次。由于电影《速度与激情》的剧本包含了许多不被认为是标准英语的单词和短语,翻译人员更倾向于逐字逐句的翻译过程,这是有道理的。由于它采用的是对等法而不是直译法,因此比直译法更灵活
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Translation Techniques Used in Translating Non- Standard English Words in The Fast and Furious Movie
This study examines the translation approaches utilized to translate non-standard English in The Fast and the Furious: Tokyo Drift's screenplay. This study employed qualitative methods. In this study, the researcher assessed the translation technique of 102 non-standard English words from the script for The Fast and the Furious: Tokyo Drift. Molina and Albir's notion of translation procedures was utilized by the researchers. In this study, the researcher found 9 kinds of translation techniques such as literal, established equivalent, adaptation, borrowing, linguistic compression, generalization, reduction, linguistic amplification, particularization. Moreover, the dominant translation technique is literal translation technique used 35 times with percentage 54,61%% from the data, followed by established equivalent 18,44% used 13 times, adaptation with 7,15% used 5 times, borrowing with 7,15% percentage from the data used 5 times, linguistic compression with percentage 3,57% used 3 times, generalization used 2 times with percentage 2,75%, reduction used 2 times with percentage 2,75%, linguistic amplification used 1 time with percentage 1,79%, and particularization percentage 1,79% used 1 time. Since the script for the Fast and the Furious movie contains many words and phrases that are not considered standard English, it makes sense that the translators would prefer the literal translation process, which includes providing an exact word-for-word counterpart. Because it uses an equivalence-based approach rather than a literal one, this method is more flexible than literal translation
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