We describe our recently developed neural machine translation (NMT) system and benchmark it against our own statistical machine translation (SMT) system as well as two other general purpose online engines (statistical and neural). We present automatic and human evaluation results of the translation output provided by each system. We also analyze the effect of sentence length on the quality of output for SMT and NMT systems.
@article{arxiv.1707.07911,
title = {Machine Translation at Booking.com: Journey and Lessons Learned},
author = {Pavel Levin and Nishikant Dhanuka and Maxim Khalilov},
journal= {arXiv preprint arXiv:1707.07911},
year = {2017}
}
Comments
6 pages, 8 figures, 2 tables. In proceedings of EAMT 2017. Prague, Czech Republic