In later sections, we will analyze the semantic information learned by the model through some visualization examples, shown in section 5.1, and the experimental results show that it achieves sufficient accuracy for scoring the alignment between source and target sentences.
in our framework, G aims to generate a translation score higher than the golden-standard, under the premise of encoders and the scoring function learned by D. for each sentence pairs (X, Y + ) in training sets, first, G samples transla-tionŶ given X with greedy searching.