An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss

Understand

Affect conveys important implicit information in human communication.

• Having the capability to correctly express affect during human-machine conversations is one of the major milestones in artificial intelligence.
• In recent years, extensive research on open-domain neural conversational models has been conducted.
• However, embedding affect into such models is still under explored.