EAGER: A hybrid dialogue system architecture for symbolic control of deep learning networks

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Technological advances in the last fifteen years have brought conversational assistants like Siri and Alexa to society at large. While such assistants are successful at supporting well-specified tasks, their understanding of what the user truly wants is still limited, their answers can be incorrect, repetitive, or biased, and it is often hard to explain how they arrived at a certain answer. Their success depends on harvesting huge amounts of data and uncovering statistical patterns; however, very little data exists for conversations whose purpose is education or advice-giving, such as patient-healthcare educator interactions. This EArly Grant for Exploratory Research (EAGER) investigates novel dialogue system architectures that combine strategies designed by experts with the powerful statistical models of today, but applied to small datasets. If successful, this research will provide a new approach to develop culturally competent conversational assistants for many applications where users, especially from underrepresented groups, seek advice or knowledge.This EAGER project will explore new inference mechanisms that combine symbolic and neural approaches for the development of conversational assistants. We will develop an architecture which blends an explicitly designed dialogue manager module, with the effective neural encoder/decoder approaches of today. A symbolic dialogue manager will provide control over the outputs from the system and will help explain the system's decisions. Additionally, it will inherently ameliorate the need for a large dataset, since explicit expert insights can be used rather than emerge as latent variables. At the same time, we will explore how modern meaning representations combined with data augmentation models can be used to develop a larger corpus. The motivation for this research is culturally competent patient education, which is vital to better health outcomes especially in minority groups.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.