  In this paper, we introduce a high-quality and large-scale benchmark dataset
for English-Vietnamese speech translation with 508 audio hours, consisting of
331K triplets of (sentence-lengthed audio, English source transcript sentence,
Vietnamese target subtitle sentence). We also conduct empirical experiments
using strong baselines and find that the traditional "Cascaded" approach still
outperforms the modern "End-to-End" approach. To the best of our knowledge,
this is the first large-scale English-Vietnamese speech translation study. We
hope both our publicly available dataset and study can serve as a starting
point for future research and applications on English-Vietnamese speech
translation. Our dataset is available at https://github.com/VinAIResearch/PhoST

Computation and Language