Inspired by studies on the overwhelming presence of experience-sharing in human- human conversations, Emora, the social chatbot developed by Emory University, aims to bring such experience-focused interaction to the current field of conver- sational AI. The traditional approach of information-sharing topic handlers is balanced with a focus on opinion-oriented exchanges that Emora delivers, and new conversational abilities are developed that support dialogues that consist of a collaborative understanding and learning process of the partner’s life experiences. We present a curated dialogue system that leverages highly expressive natural lan- guage templates, powerful intent classification, and ontology resources to provide an engaging and interesting conversational experience to every user.
