DREAM technical report for the Alexa Prize 2019
Building a dialogue system able to talk fluently and meaningfully in an open domain conversation is one of the foundational challenges in the field of AI. Recent progress in NLP driven by the application of the deep neural networks and large language models opened new possibilities to solve many hard problems of the conversational AI. Alexa Prize Socialbot Grand Challenge gives a unique opportunity to test cutting edge research ideas in the real-world setting. In this report, we outline the DREAM socialbot solution and present evaluation results. DREAM socialbot is implemented as a multi-skill conversational agent with the modular micro-service architecture. DREAM agent orchestrates a dozen text preprocessing annotators and more than 25 conversational skills to generate responses in the context of the open domain conversation. Feedback from Alexa users during the evaluation period allowed us to gradually develop our solution by increasing the number of conversational skills and improving the transition between them. As a result, dialogues became 50% longer, and average rating grew from ∼ 3 during the initial stage in December’19 to ∼ 3.4 during the last two weeks of April’20. The final version of DREAM socialbot is a hybrid system that combines rule-based, deep learning, and knowledge base driven components.