Open Questions for Next Generation Chatbots

Abstract

Over the last few years, there has been a growing interest in developing chatbots that can converse intelligently with humans. For example, consider Microsoft’s Xiaoice. It is a highly intelligent dialogue system that serves as both a social companion and a virtual assistant. Targeted towards Chinese users, Xiaoice is connected to 660 million online users and 450 million IoT devices. Because of the deep learning revolution, the field is moving quickly, so this survey aims to introduce newcomers to the most fundamental research questions for next generation neural dialogue systems. In particular, our analysis of the state of the art reveals the following 4 key research challenges: 1) knowledge grounding, 2) persona consistency, 3) emotional intelligence, and 4) evaluation. Knowledge grounding endows the chatbot with external knowledge to generate more informative replies. Persona consistency grants dialogue systems consistent personalities. We divide each fundamental research challenge into several smaller and more concrete research questions. For each fine grained research challenge, we examine state of the art approaches and propose future research directions.