A Case Study on Contextual Machine Translation in a Professional Scenario of Subtitling
Sebastian Vincent, Charlotte Prescott, Chris Bayliss, Chris Oakley, Carolina Scarton
Abstract
Incorporating extra-textual context such as film metadata into the machine translation (MT) pipeline can enhance translation quality, as indicated by automatic evaluation in recent work. However, the positive impact of such systems in industry remains unproven. We report on an industrial case study carried out to investigate the benefit of MT in a professional scenario of translating TV subtitles with a focus on how leveraging extra-textual context impacts post-editing. We found that post-editors marked significantly fewer context-related errors when correcting the outputs of MTCue, the context-aware model, as opposed to non-contextual models. We also present the results of a survey of the employed post-editors, which highlights contextual inadequacy as a significant gap consistently observed in MT. Our findings strengthen the motivation for further work within fully contextual MT.- Anthology ID:
- 2024.eamt-1.46
- Volume:
- Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)
- Month:
- June
- Year:
- 2024
- Address:
- Sheffield, UK
- Editors:
- Carolina Scarton, Charlotte Prescott, Chris Bayliss, Chris Oakley, Joanna Wright, Stuart Wrigley, Xingyi Song, Edward Gow-Smith, Rachel Bawden, Víctor M Sánchez-Cartagena, Patrick Cadwell, Ekaterina Lapshinova-Koltunski, Vera Cabarrão, Konstantinos Chatzitheodorou, Mary Nurminen, Diptesh Kanojia, Helena Moniz
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation (EAMT)
- Note:
- Pages:
- 561–572
- Language:
- URL:
- https://aclanthology.org/2024.eamt-1.46
- DOI:
- Cite (ACL):
- Sebastian Vincent, Charlotte Prescott, Chris Bayliss, Chris Oakley, and Carolina Scarton. 2024. A Case Study on Contextual Machine Translation in a Professional Scenario of Subtitling. In Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1), pages 561–572, Sheffield, UK. European Association for Machine Translation (EAMT).
- Cite (Informal):
- A Case Study on Contextual Machine Translation in a Professional Scenario of Subtitling (Vincent et al., EAMT 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.eamt-1.46.pdf