Syntax-based data augmentation for Hungarian-English machine translation
Computation and Language
2022-01-19 v1 Machine Learning
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.
Keywords
Cite
@article{arxiv.2201.06876,
title = {Syntax-based data augmentation for Hungarian-English machine translation},
author = {Attila Nagy and Patrick Nanys and Balázs Frey Konrád and Bence Bial and Judit Ács},
journal= {arXiv preprint arXiv:2201.06876},
year = {2022}
}