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Strategies of translating swear words into Arabic: a case study of a parallel corpus of Netflix English-Arabic movie subtitles
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Strategies of translating swear words into Arabic: a case study of a parallel corpus of Netflix English-Arabic movie subtitles
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Strategies of translating swear words into Arabic: a case study of a parallel corpus of Netflix English-Arabic movie subtitles
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Journal Article
Strategies of translating swear words into Arabic: a case study of a parallel corpus of Netflix English-Arabic movie subtitles
2023
Overview
This study adopts a corpus-assisted approach to explore the translation strategies that Netflix subtitlers opted for in rendering 1564 English swear words into Arabic. It uses a 699,229-word English-Arabic parallel corpus consisting of the English transcriptions of forty English movies, drama, action, science fiction (sci-fi), and biography and their Arabic subtitles. Using the wordlist tool in SketchEngine, the researchers identified some frequent swear words, namely fuck, shit, damn, ass, bitch, bastard, asshole, dick, cunt , and pussy . Moreover, using the parallel concordance tool in SketchEngine revealed that three translation strategies were observed in the corpus, namely, omission, softening, and swear-to-non-swear. The omission strategy accounted for the lion’s share in the investigated data, with 66% for drama, 61% for action, 52% for biography, and 40% for sci-fi. On the other hand, the swear-to-non-swear strategy was the least adopted one, accounting for 21% in sci-fi, 16% in biography, 14% in drama, and 11% in action. In addition, the softening strategy got the second-highest frequency across the different movie genres, with 39% for sci-fi, 32% for biography, 28% for action, and 20% for drama. Since swear words have connotative functions, omitting or euphemizing them could cause a slight change in the representation of meaning and characters. The study recommends more corpus-assisted studies on different AVT modes, including dubbing, voiceover, and free commentaries.
