NRC Machine Translation System for WMT 2017

摘要

We describe the machine translation systems developed at the National Research Council of Canada (NRC) for the Russian-English and Chinese-English news translation tasks of the Second Conference on Machine Translation (WMT 2017). We conducted several experiments to explore the best baseline settings for neural machine translation (NMT). In the Russian-English task, to our surprise, our best-performing system is one that rescores phrase-based statistical machine translation outputs using NMT rescoring features. On the other hand, in the Chinese-English task, which has far more parallel training data, NMT is able to outperform SMT significantly. The NRC MT systems is the best constrained system in Russian-English (out of nine participants) and the fourth best constrained system in Chinese-English (out of twenty participants) in WMT 2017 human evaluation.