The Role of Sound in Film Translation: Subtitling Embodied Aural Experience in Aki Kaurismäki’s Lights in the Dusk
Bibliographic record
Abstract
The purpose of this article is twofold. First, by adopting a film studies-oriented approach to AVT it seeks to build common ground between translation studies and film studies—two disciplines that have remained curiously distant from each other, even though the film and translation industries are closely interrelated at the practical level. Second, by introducing study of the aural dimension of audiovisual texts—in particular film sound—to AVT, this article presents a new concept of text for AVT research that allows for the analysis of audiovisual texts as dynamic entities consisting of the visual, the aural and the verbal. These are seen as equally important constituent parts of audiovisual texts; they do not simply coexist but transform each other at the moment of perception. The role of sound in film translation is examined by applying phenomenologically informed theories of film sound, mainly Michel Chion’s (1994) theory of audio-vision, to the context of film subtitling. According to Chion, film viewing is based on cross-modal perception, i.e. synchronous sound and image are experienced as a unit, a “synchresis” (ibid., p. 63). Chion argues that filmic image and sound transform each other at the moment of perception, producing added value (ibid., p. 5). These audiovisual combinations not only address the viewer at the conceptual level but also contribute to the intensity and flow of the viewing experience that is to a large extent conveyed non-verbally. This paper argues that the translator’s decisions influence the added value created by image and sound and direct the viewer’s perception of a film, often overemphasizing the verbal element, thus narrowing the film’s non-verbally conveyed meanings and decreasing its emotional and esthetic appeal. These points are illustrated by presenting examples of the English and German subtitled versions of Aki Kaurismäki’s film Laitakaupungin valot (Lights in the Dusk).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".