title: Modeling all dialogue system participants to generate empathetic responses.
abstract: A dialogue system between an expert system and its users is described which combines two recent hypotheses. First, that the dialogue system should explicitly model both the person directly interacting with the dialogue system (the agent) and the person reasoned about by the expert system (the patient) in order to communicate meaningfully with both people. Second, that a dialogue system can model the domain-related beliefs, preferences and concerns of both its users and generate responses empathetic to both. This dialogue system is called SERUM, standing for 'System for Empathetic Responses with User Models.' SERUM generates natural-language responses about attribute values of domain objects, via three transformations. First, the system converts properties of the agent and patient, and domain knowledge, into a pragmatic objective like empathy. Second, SERUM converts the pragmatic objectives into surface structure cues like object emphasis and level of technicality. Finally, SERUM converts the surface structure cues to realize text that is natural, appropriately technical and emotionally empathetic. SERUM is demonstrated in describing tests and treatments for lung disease in AIDS patients, a sensitive domain where empathetic responses may be needed.
authors.affiliation: MIT Laboratory for Computer Science, Cambridge, MA 02139.
authors.forename: I J
authors.initials: IJ
authors.lastname: Haimowitz
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005103:Expert Systems; D008962:Models, Theoretical; D012985:Software Design; D009626:Terminology as Topic; D014584:User-Computer Interface