Machine Translation at Booking.com: Journey and Lessons Learned
This work addresses translation quality for a travel booking platform, but it is incremental as it benchmarks existing methods without introducing new paradigms.
The authors tackled the problem of improving machine translation at Booking.com by developing a neural machine translation (NMT) system and benchmarking it against their own statistical machine translation (SMT) system and other online engines, resulting in evaluation of translation quality and analysis of sentence length effects.
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.