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PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation

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arxiv 2110.12199 v1 pith:FZZADBUA submitted 2021-10-23 cs.CL

Long Doan , Linh The Nguyen , Nguyen Luong Tran , Thai Hoang , Dat Quoc Nguyen This is my paper · ORCID
classification cs.CL
keywords translationvietnamese-englishdatasetmachinelarge-scaleautomaticbenchmarkbest
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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.

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  1. An Efficient Approach for Machine Translation on Low-resource Languages: A Case Study in Vietnamese-Chinese

    cs.CL 2025-01 conditional novelty 4.0 of 10

    Fine-tuning mBART with TF-IDF-selected back-translated monolingual sentences raises test BLEU from 38.22 to 38.97 for Vietnamese-to-Chinese and from 35.58 to 38.90 for Chinese-to-Vietnamese.

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