A Modular Data-Driven Architecture for Empathetic Conversational Agents

Empathy is a fundamental mechanism of human interactions. As such, it should be an integral part of Human-Computer Interaction systems to make them more relatable. With this work, we focused on conversational scenarios where integrating empathy is crucial to perceive the computer as a human. As a result, we derived the high-level architecture of an Empathetic Conversational Agent we are willing to implement. We relied on theories about artificial empathy to derive the function approximating this mechanism, and selected the con- versational aspects to control for an empathetic interaction. In particular, a core empathetic controller manages the empathetic responses, predicting, at each turn, the high-level content of the response. The derived architecture integrates empathy in a task-agnostic manner, hence we can employ it in multiple scenarios by changing the objective of the controller.