Syntax-based data augmentation for Hungarian-English machine translation
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 26 references that are in the map. First posted on arXiv 18 Jan 2022.
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