Generating Persona Consistent Dialogues by Exploiting Natural Language Inference
Table 3: Automatic results, and Dst. is scaled by 10−4.
['[BOLD] Model', '[BOLD] ppl', '[BOLD] Ave.', '[BOLD] Grd.', '[BOLD] Ext.', '[BOLD] Dst.']
Our methods are the best in the three embedding metrics, which indicates that our generated responses are most relevant to the ground truth. As our model is designed to address naturalness and consistency issues effectively, these results are within expectation. We notice that Transformer gets the best results in perplexity and distinct-2. It could be interpreted to mean that Transformer has a better language model compared with all other RNN based models. This also inspires us to use more advanced sequence models as our generator in future work. Except for the Transformer, our methods perform best in these RNN-based models.