NRC Machine Translation System for WMT 2017
Chi-kiu Lo, Boxing Chen, Colin Cherry, George Foster, Samuel Larkin, Darlene A. Stewart, Roland Kühn · 2017
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 bestperforming 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.