Mixed initiative dialog via structured knowledge graph traversal and conversational scaffolding
We present BYU-EVE, an open domain dialogue architecture that combines the strengths of hand-crafted rules, deep learning, and structured knowledge graph traversal in order to create satisfying user experiences. Rather than viewing dialogue as a strict mapping between input and output texts, EVE treats conversations as a collaborative process in which two jointly coordinating agents chart a trajectory through experiential space. A key element of this architecture is the use of conversational scaffolding, a technique which uses a (small) conversational dataset to define a generalized response strategy. We also take the innovative approach of integrating the agent’s self and user models directly within the knowledge graph. This allows EVE to discern topics of shared interest while simultaneously identifying areas of ambiguity or cognitive dissonance.