Paper ID: 2201.06876

Syntax-based data augmentation for Hungarian-English machine translation

Attila Nagy, Patrick Nanys, Balázs Frey Konrád, Bence Bial, Judit Ács

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.

Submitted: Jan 18, 2022