Slugbot: An Application of a Novel and Scalable Open Domain Socialbot Framework
This work addresses the challenge of creating scalable and friendly conversational AI for general users, though it appears incremental as it builds on existing frameworks and tools.
The authors tackled the problem of building an open-domain socialbot for the Amazon Alexa Prize competition, resulting in a modular system that uses natural language understanding and information retrieval tools to manage conversations on various topics, with performance briefly evaluated and challenges noted.
In this paper we introduce a novel, open domain socialbot for the Amazon Alexa Prize competition, aimed at carrying on friendly conversations with users on a variety of topics. We present our modular system, highlighting our different data sources and how we use the human mind as a model for data management. Additionally we build and employ natural language understanding and information retrieval tools and APIs to expand our knowledge bases. We describe our semistructured, scalable framework for crafting topic-specific dialogue flows, and give details on our dialogue management schemes and scoring mechanisms. Finally we briefly evaluate the performance of our system and observe the challenges that an open domain socialbot faces.