A Neural Topical Expansion Framework for Unstructured Persona-oriented Dialogue Generation
Table 2: Automatic evaluation results. The best results are bold.
['[BOLD] Model', '[BOLD] BLEU1', '[BOLD] BLEU2', '[BOLD] BLEU3', '[BOLD] BLEU4', '[BOLD] F1', '[BOLD] Average', '[BOLD] Extrema', '[BOLD] Greedy']
Our model outperforms baselines on all automatic metrics. This demonstrates that our model generates more appropriate responses by persona exploration and exploitation. Especially, our model improves approximately 15.17% over seq2seq on BLEU1. Comparing with PED, PED+PE has better scores on most metrics. This is because explored persona information contributes to generate more informative responses. Comparing with PED+PE, both PED+PE+p-BoWs and PED+PE+P-Match perform better, which is because P-BoWs loss and P-Match loss supervise model to exploit persona information more precisely.