  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.
