Many impressive progresses have been made in neural machine translation (NMT) in the past few years (Luong et al., 2015; Gehring et al., 2017; Vaswani et al., 2017; Wu et al., 2019).
the general training procedure requires tremendous amounts of high-quality parallel corpus to achieve a deep model's full potential.