Improving Vietnamese-English Medical Machine Translation
Nhu Vo, Dat Quoc Nguyen, Dung D. Le, Massimo Piccardi, Wray Buntine
Abstract
Machine translation for Vietnamese-English in the medical domain is still an under-explored research area. In this paper, we introduce MedEV—a high-quality Vietnamese-English parallel dataset constructed specifically for the medical domain, comprising approximately 360K sentence pairs. We conduct extensive experiments comparing Google Translate, ChatGPT (gpt-3.5-turbo), state-of-the-art Vietnamese-English neural machine translation models and pre-trained bilingual/multilingual sequence-to-sequence models on our new MedEV dataset. Experimental results show that the best performance is achieved by fine-tuning “vinai-translate” for each translation direction. We publicly release our dataset to promote further research.- Anthology ID:
- 2024.lrec-main.784
- 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:
- 8955–8962
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.784
- DOI:
- Cite (ACL):
- Nhu Vo, Dat Quoc Nguyen, Dung D. Le, Massimo Piccardi, and Wray Buntine. 2024. Improving Vietnamese-English Medical Machine Translation. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 8955–8962, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Improving Vietnamese-English Medical Machine Translation (Vo et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.784.pdf