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arXiv · 2201.06876

Syntax-based data augmentation for Hungarian-English machine translation

Attila Nagy·Patrick Nanys·Balázs Frey Konrád·Bence Bial·Judit Ács
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Abstract

We train Transformer-based neural machine translation models for Hungarian-English and English-Hungarian using the Hunglish2 corpus. Our best models achieve a BLEU score of 40.0 on HungarianEnglish and 33.4 on English-Hungarian. Furthermore, we present results on an ongoing work about syntax-based augmentation for neural machine translation. Both our code and models are publicly available.

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Attila Nagy, Patrick Nanys, Balázs Frey Konrád, Bence Bial, Judit Ács. 2022-01-18. Syntax-based data augmentation for Hungarian-English machine translation. https://arxiv.org/abs/2201.06876

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