Our ability to communicate using language in conversation is considered the hallmark of human intelligence. Yet, while holding a dialogue is effortless for most of us, modelling this basic human skill by computational means has proven extremely difficult. DREAM combines insights from linguistic and cognitive theories of human dialogue with machine learning techniques to develop artificial conversational agents that learn directly from data about human language use and are more human-like.
Artificial conversational agents, such as chatbots and personal assistants, are increasingly present in our everyday lives. Many websites now for instance host customer service chatbots, and dialogue agents are also being used in education and health coaching. Interacting with these systems already feels a lot more natural and is less frustrating for the user than ten or even five years ago; nevertheless, there is substantial room for improvement. In DREAM, we aim to (1) deepen our understanding of what features of human conversations are key and should be incorporated in our artificial dialogue systems, and (2) develop machine models implemented as artificial neural networks that lead to dialogue agents that incorporate these features -- for example, being able to adapt to the user and to integrate visual and linguistic information.
DREAM is hosted by the Institute for Logic, Language & Computation (ILLC), Faculty of Science, University of Amsterdam.