Abstract:
Daily communication is influenced by many factors. These factors allow conversational systems to generate positive responses and build friendly relationships with users. This study examines emotion and intention as response generators. We create a hierarchical variational model to investigate their relationship. Based on predictions, the response can be word-by-word. A novel adversarial-augmented inference network aids model training. The proposed model and adversarial objective work well in experiments. The emotion-communication hypothesis is also supported.
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