An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation
Table 1: BLEU scores for the AEM model and the Seq2Seq model.
['Models', 'BLEU-1', 'BLEU-2', 'BLEU-3', 'BLEU-4']
We use BLEU Papineni et al. The proposed AEM model significantly outperforms the Seq2Seq model. It demonstrates the effectiveness of utterance-level dependency on improving the quality of generated text. Furthermore, we find that the utterance-level dependency also benefits the learning of word-level dependency. It is much more obvious than the improvement from the Seq2Seq model to the Seq2Seq+Attention, which is 0.29 BLEU-4 point.