  Conversational Intelligence requires that a person engage on informational,
personal and relational levels. Advances in Natural Language Understanding have
helped recent chatbots succeed at dialog on the informational level. However,
current techniques still lag for conversing with humans on a personal level and
fully relating to them. The University of Michigan's submission to the Alexa
Prize Grand Challenge 3, Audrey, is an open-domain conversational chat-bot that
aims to engage customers on these levels through interest driven conversations
guided by customers' personalities and emotions. Audrey is built from
socially-aware models such as Emotion Detection and a Personal Understanding
Module to grasp a deeper understanding of users' interests and desires. Our
architecture interacts with customers using a hybrid approach balanced between
knowledge-driven response generators and context-driven neural response
generators to cater to all three levels of conversations. During the
semi-finals period, we achieved an average cumulative rating of 3.25 on a 1-5
Likert scale.
