Reference-less Analysis of Context Specificity in Translation with Personalised Language Models
Sebastian Vincent, Rowanne Sumner, Alice Dowek, Charlotte Prescott, Emily Preston, Chris Bayliss, Chris Oakley, Carolina Scarton
Abstract
Sensitising language models (LMs) to external context helps them to more effectively capture the speaking patterns of individuals with specific characteristics or in particular environments. This work investigates to what extent detailed character and film annotations can be leveraged to personalise LMs in a scalable manner. We then explore the use of such models in evaluating context specificity in machine translation. We build LMs which leverage rich contextual information to reduce perplexity by up to 6.5% compared to a non-contextual model, and generalise well to a scenario with no speaker-specific data, relying on combinations of demographic characteristics expressed via metadata. Our findings are consistent across two corpora, one of which (Cornell-rich) is also a contribution of this paper. We then use our personalised LMs to measure the co-occurrence of extra-textual context and translation hypotheses in a machine translation setting. Our results suggest that the degree to which professional translations in our domain are context-specific can be preserved to a better extent by a contextual machine translation model than a non-contextual model, which is also reflected in the contextual model’s superior reference-based scores.- Anthology ID:
- 2024.lrec-main.1202
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 13769–13784
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.1202
- DOI:
- Cite (ACL):
- Sebastian Vincent, Rowanne Sumner, Alice Dowek, Charlotte Prescott, Emily Preston, Chris Bayliss, Chris Oakley, and Carolina Scarton. 2024. Reference-less Analysis of Context Specificity in Translation with Personalised Language Models. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 13769–13784, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Reference-less Analysis of Context Specificity in Translation with Personalised Language Models (Vincent et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2024.lrec-main.1202.pdf