Swearword strength in subtitled and dubbed films: A reception study
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Lucia Briechle
Lucia Briechle has recently started her own business as a freelancer translator for medical and audiovisual texts. Her research is motivated by the belief that target audiences should have an as similar as possible audiovisual experience as source audiences. She targets gaps in translation practices, such as the translation of swearing, and by narrowing such gaps through empirical research, she aims to improve the AV experiences of target audiences.
Eva Duran Eppler is Associate Professor of Linguistics at the University of Roehampton, London, UK. Her main research area is structural and processing aspects of multilingualism. She has published extensively in this area, e.g.
Emigranto (New Academic Press, 2010). Her recent projects also involve linguistic aspects of translation, e.g. The deliberate non-translation of L3s inBreaking Bad , Meta 63(2), 2018.
Abstract
In this paper we present the results of the first empirical reception study on the comparative strength of swearwords in two audiovisual translation (AVT) modes. We test the assumption/hypothesis that swearwords are perceived as stronger in writing (i.e. subtitles) than in spoken language (i.e. dubbing), which has led to the long-held translation practice of toning down or deleting swearwords more in subtitles than in dubbing. By means of an online survey, participants were asked to a) rate the psychological distance between the connotative meanings of swearwords embedded in ten film clips on a four-point strength scale, and b) comment on their ratings in open-ended text boxes. The results of various types of quantitative analysis show that our participants do not rate swearwords in subtitles higher than in dubbed clips. The qualitative analysis identified contextual factors (genre/director of film, participating characters and their relationship, setting and linguistic context) as well as viewer characteristics (gender, swearing habits and reactions to swearing) as main determinants of swearword strength. The convention of toning down or deleting swearwords more in subtitles than in dubbed audiovisual products thus seems to be based on an invalid assumption and ought to be abandoned altogether.
About the authors
Lucia Briechle has recently started her own business as a freelancer translator for medical and audiovisual texts. Her research is motivated by the belief that target audiences should have an as similar as possible audiovisual experience as source audiences. She targets gaps in translation practices, such as the translation of swearing, and by narrowing such gaps through empirical research, she aims to improve the AV experiences of target audiences.
Eva Duran Eppler is Associate Professor of Linguistics at the University of Roehampton, London, UK. Her main research area is structural and processing aspects of multilingualism. She has published extensively in this area, e.g. Emigranto (New Academic Press, 2010). Her recent projects also involve linguistic aspects of translation, e.g. The deliberate non-translation of L3s in Breaking Bad, Meta 63(2), 2018.
Acknowledgements
We would like to thank Marika Kulesza and Daniel Rukstelis for their stats support, our reviewers for their valuable feedback and the editor for a smooth publication process.
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Appendix A
The clips from these films used in this survey are available on Google Drive https://drive.google.com/drive/folders/1Y7CWfxEvjG3WBpV8idSbIHd-kPgpZgJ_
Appendix B
Individual pairwise comparisons of all swearwords in both AVT modes
| SW | Qu no + sub vs. dub | Mean sub | Mean dub | Z scores | p values | Bonferoni | Sig @ 0.05 |
|---|---|---|---|---|---|---|---|
| Arsch | 41sub vs. 27sub | 1.81 | 1.78 | −0.551 | 0.582 | 0.0083 | NS |
| 27sub vs. 14 dub | 1.78 | 2.01 | −2.902 | 0.004 | 0.0083 | * | |
| 27sub vs. 33dub | 1.78 | 2.17 | −4.625 | 0.000 | 0.0083 | ** | |
| 41sub vs. 14 dub | 1.81 | 2.01 | −2.111 | 0.035 | 0.0083 | NS | |
| 41sub vs. 33dub | 1.81 | 2.17 | −4.449 | 0.000 | 0.0083 | ** | |
| 33dub vs.14 dub | 2.17 | 2.01 | −1.960 | 0.050 | 0.0083 | NS | |
| 27 + 41sub avg vs. 14 + 33dub avg | 1.79 | 2.09 | −4.511 | 0.000 | n/a | ** | |
| Arschgesicht | 46dub | 2.31 | – | – | – | – | – |
| Arschloch | 29sub vs. 17dub | 2.17 | 1.98 | −2.333 | 0.020 | n/a | * |
| Leck mich (am Arsch) | 32dub | – | 2.28 | – | – | – | – |
| Fick(en) vs (ge)fick(t) | 48sub vs. 44dub | 2.42 | 2.35 | 0.857 | 0.391 | n/a | NS |
| Idiot | 8sub | 1.80 | – | – | – | – | – |
| (bloede) Kuh | 31dub | – | 1.46 | – | – | – | – |
| Makkaroniziege | 34dub | – | 2.01 | – | – | – | – |
| Mist | 30sub vs. 24dub | 1.31 | 1.16 | −2.826 | 0.005 | n/a | * |
| Mistkerl | 6sub vs. 42sub | 1.45 | 1.61 | −1.670 | 0.095 | 0.0167 | NS |
| 6sub vs. 18dub | 1.45 | 1.51 | −0.997 | 0.319 | 0.0167 | NS | |
| 42sub vs. 18dub | 1.61 | 1.53 | −1.121 | 0.262 | 0.0167 | NS | |
| 6 + 42sub avg vs. 18dub | 1.53 | 1.53 | −0.021 | 0.983 | n/a | NS | |
| Nigger | 9sub vs. 43dub | 3.28 | 2.58 | −5.495 | 0.000 | n/a | ** |
| Nutte | 38dub | – | 2.86 | – | – | – | – |
| Scheisse | 15sub vs. 12dub | 1.34 | 1.91 | −2.937 | 0.000 | 0.0167 | ** |
| 15sub vs. 20dub | 1.34 | 1.52 | −2.937 | 0.003 | 0.0167 | * | |
| 12dub vs. 20dub | 1.91 | 1.52 | −4.021 | 0.000 | 0.0167 | ** | |
| 15sub vs. 12 + 20dub avg | 1.34 | 1.71 | −4.728 | 0.000 | n/a | ** | |
| scheissegal | 10dub | – | 1.70 | – | – | – | – |
| Schlampe | 47sub vs. 35dub | 2.57 | 2.95 | −4.475 | 0.000 | 0.0167 | ** |
| 47sub vs. 19dub | 2.57 | 2.84 | −3.305 | 0.001 | 0.0167 | * | |
| 19dub vs. 35dub | 2.84 | 2.95 | −1.704 | 0.088 | 0.0167 | NS | |
| 47sub vs. 19 + 35 dub avg | 2.57 | 2.89 | −4.268 | 0.000 | n/a | ** | |
| Schwanz | 25sub | 2.07 | – | – | – | – | – |
| Schwanzlutscher | 22dub | – | 2.65 | – | – | – | – |
| Schwein | 7sub vs. 39sub | 2.17 | 1.85 | −2.879 | 0.004 | 0.0167 | * |
| 7sub vs. 37dub | 2.17 | 1.92 | −2.197 | 0.028 | 0.0167 | NS | |
| 39sub vs. 37dub | 1.85 | 1.92 | −0.965 | 0.335 | 0.0167 | NS | |
| 7 + 39sub avg vs. 37dub | 2.01 | 1.92 | −1.180 | 0.238 | n/a | NS | |
| schwul | 13dub | – | 2.61 | – | – | – | – |
| 23dub | – | 2.22 | – | – | – | – | |
| 13dub vs. 23dub | – | 2.42 | −4.057 | 0.000 | n/a | ** | |
| Tunte | 21sub | 2.34 | – | – | – | – | – |
| Trottel | 26sub | 1.55 | – | – | – | – | – |
| verdammt | 16sub vs. 28sub | 1.23 | 1.31 | −1.377 | 0.168 | 0.0083 | NS |
| 16sub vs. 40sub | 1.23 | 1.42 | −3.541 | 0.000 | 0.0083 | ** | |
| 16sub vs. 36dub | 1.23 | 1.50 | −3.998 | 0.000 | 0.0083 | ** | |
| 28sub vs. 40sub | 1.31 | 1.42 | −2.083 | 0.037 | 0.0083 | NS | |
| 28sub vs. 36dub | 1.31 | 1.49 | −2.865 | 0.004 | 0.0083 | * | |
| 40sub vs. 36dub | 1.42 | 1.49 | −1.265 | 0.206 | 0.0083 | NS | |
| 16 + 28 + 40sub avg vs 36dub | 1.32 | 1.49 | −3.359 | 0.001 | n/a | * | |
| Wichser | 45sub vs. 11dub | 2.50 | 2.65 | −1.72 | 0.085 | n/a | NS |
© 2019 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- research-article
- A modality-based approach to the United Nations Security Council’s ambiguous positioning in the resolutions on the Syrian armed conflict
- Swearword strength in subtitled and dubbed films: A reception study
- Pragmatics in the interpretation of scope ambiguities
- Forum
- Indirect reports as semantic-pragmatic games
- book-review
- Rachel Giora Michael Haugh: Doing Pragmatics Interculturally: Cognitive, Philosophical, and Sociopragmatic Perspectives
- Jonathan Culpeper Michael Haugh Dániel Z. Kádár: The Palgrave Handbook of Linguistic (Im)politeness
Articles in the same Issue
- Frontmatter
- research-article
- A modality-based approach to the United Nations Security Council’s ambiguous positioning in the resolutions on the Syrian armed conflict
- Swearword strength in subtitled and dubbed films: A reception study
- Pragmatics in the interpretation of scope ambiguities
- Forum
- Indirect reports as semantic-pragmatic games
- book-review
- Rachel Giora Michael Haugh: Doing Pragmatics Interculturally: Cognitive, Philosophical, and Sociopragmatic Perspectives
- Jonathan Culpeper Michael Haugh Dániel Z. Kádár: The Palgrave Handbook of Linguistic (Im)politeness
