| Title | A Modular Data-Driven Architecture for Empathetic Conversational Agents |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Scotti, Vincenzo, Tedesco, Roberto, Sbattella, Licia |
| Conference Name | 2021 IEEE International Conference on Big Data and Smart Computing (BigComp) |
| Date Published | jan |
| Keywords | Big Data, Computer architecture, Conferences, conversational agents, Deep Learning, Empathetic Computing, Human Behavior, human computer interaction, Metrics, pubcrawl, Scalability, Task Analysis |
| Abstract | 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 like 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 conversational aspects to control for an empathetic interaction. In particular, we designed 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. |
| DOI | 10.1109/BigComp51126.2021.00080 |
| Citation Key | scotti_modular_2021 |
A Modular Data-Driven Architecture for Empathetic Conversational Agents