%0 Conference Proceedings %T PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation %A Doan, Long %A Nguyen, Linh The %A Tran, Nguyen Luong %A Hoang, Thai %A Nguyen, Dat Quoc %Y Moens, Marie-Francine %Y Huang, Xuanjing %Y Specia, Lucia %Y Yih, Scott Wen-tau %S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing %D 2021 %8 November %I Association for Computational Linguistics %C Online and Punta Cana, Dominican Republic %F doan-etal-2021-phomt %X We introduce a high-quality and large-scale Vietnamese-English parallel dataset of 3.02M sentence pairs, which is 2.9M pairs larger than the benchmark Vietnamese-English machine translation corpus IWSLT15. We conduct experiments comparing strong neural baselines and well-known automatic translation engines on our dataset and find that in both automatic and human evaluations: the best performance is obtained by fine-tuning the pre-trained sequence-to-sequence denoising auto-encoder mBART. To our best knowledge, this is the first large-scale Vietnamese-English machine translation study. We hope our publicly available dataset and study can serve as a starting point for future research and applications on Vietnamese-English machine translation. We release our dataset at: https://github.com/VinAIResearch/PhoMT %R 10.18653/v1/2021.emnlp-main.369 %U https://aclanthology.org/2021.emnlp-main.369 %U https://doi.org/10.18653/v1/2021.emnlp-main.369 %P 4495-4503