A High-Quality and Large-Scale Dataset for English-Vietnamese Speech Translation

TL;DR

This paper introduces a large-scale, high-quality English-Vietnamese speech translation dataset and compares traditional and modern translation approaches, finding the traditional method still performs better.

Contribution

It provides the first large-scale English-Vietnamese speech translation dataset and offers empirical insights into approach performance.

Findings

Traditional cascaded approach outperforms end-to-end methods

The dataset contains 508 hours of speech and 331K triplets

First large-scale English-Vietnamese speech translation study

Abstract

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