Investigating Romantic-Tone Transfers in the Human Translation Compared to AI Subtitling: A Case Study of the Dilan 1990 Film
Authors
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Fanny Puji Rakhmi
Politeknik Negeri Jakarta
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Taufik Eryadi Abdillah
Politeknik Negeri Jakarta
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Farizka Humolungo
Politeknik Negeri Jakarta
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Ina Sukaesih
Politeknik Negeri Jakarta
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Septina Indrayani
Politeknik Negeri Jakarta
DOI:
https://doi.org/10.36312/jolls.v6i1.3570Keywords:
Audiovisual translation, Dilan 1990, Neural machine translation, Romance, SubtitlingAbstract
This paper examines how romantic tone is carried across languages in film subtitling, where text must be brief, well-timed, and easy to read. We focus on Dilan 1990, a popular Indonesian teen romance known for playful, indirect lines that rely on inference and rhythm. Today, many studios generate first-pass subtitles with neural machine translation and then rely on human post-editors to refine style and timing. We ask how well AI handles this kind of subtle, affect-rich dialogue and where human editing still adds value. We compare 24 well-known lines addressed by Dilan to Milea in two versions: the official English subtitles and outputs produced by ChatGPT under the same line-level constraints. Using a practical set of translation techniques (e.g., modulation, compression, adaptation) and a tone rubric (playfulness/coyness, warmth, persona/rhythm), we perform a line-by-line analysis. The human subtitles tend to keep implicature and pace through concise, idiomatic choices that fit character and reading speed. The AI versions are fluent but more likely to explain subtext or lengthen the line, which can blunt teasing and shift the scene’s mood. AI can match human choices when the source line is already compact and direct. Where meaning depends on ellipsis, metaphor, and micro-timing, human post-editing remains crucial. We close with practical guidelines for NMT-plus-post-editing workflows in romance subtitling.
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Copyright (c) 2026 Fanny Puji Rakhmi, Taufik Eryadi Abdillah, Farizka Humolungo, Ina Sukaesih, Septina Indrayani
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