SYSTEM PERSONALITY AND ADAPTIVITY IN AFFECTIVE HUMAN-COMPUTER INTERACTION
It has been demonstrated that human users attribute a personality to the computer interfaces they use, regardless of whether one has been explicitly encoded in the system's design or not. In this paper, we explore a method for having explicit control over the personality that a spoken human-robot interface is perceived to exhibit by its users. Our method focuses on the interaction between users and semantic knowledge-based systems where the goal of the interaction is that information from the semantic store is relayed to the user. We describe a personality modelling method that complements a standard dialogue manager by calculating parameters related to adaptivity and emotion for the various interaction modules that realize the system's dialogue acts. This calculation involves the planned act, the user adaptivity model, the system's own goals, but also a machine representation of the personality that we want the system to exhibit, so that systems with different personality will react differently even when in the same dialogue state and with the same user or user type.
human-robot interfaces adaptive nlg knowledge representation