The reviewed record of science sign in
Pith

arxiv: 2210.05610 · v2 · pith:EVGD7UQ4 · submitted 2022-10-11 · cs.CL · cs.AI

MTet: Multi-domain Translation for English and Vietnamese

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:EVGD7UQ4record.jsonopen to challenge →

classification cs.CL cs.AI
keywords translationmtetvietnamesecombiningenglishenglish-vietnamesemodelmulti-domain
0
0 comments X
read the original abstract

We introduce MTet, the largest publicly available parallel corpus for English-Vietnamese translation. MTet consists of 4.2M high-quality training sentence pairs and a multi-domain test set refined by the Vietnamese research community. Combining with previous works on English-Vietnamese translation, we grow the existing parallel dataset to 6.2M sentence pairs. We also release the first pretrained model EnViT5 for English and Vietnamese languages. Combining both resources, our model significantly outperforms previous state-of-the-art results by up to 2 points in translation BLEU score, while being 1.6 times smaller.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. PiDA: Phonetically-Informed Data Augmentation for Robust Vietnamese Speech Translation

    cs.CL 2026-06 unverdicted novelty 6.0

    PiDA generates phonetically similar corruptions for fine-tuning NMT on FLEURS Vietnamese-English, improving translation of ASR errors by up to +2.04 BLEU while slightly boosting clean performance.