  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 conversational 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 language templates, powerful intent
classification, and ontology resources to provide an engaging and interesting
conversational experience to every user.
