Expressing Personalities Of Conversational Agents Through Visual And Verbal Feedback

As the uses of conversational agents increase, the affective and social abilities of agents become important with their functional abilities. Agents that lack affective abilities could frustrate users during interaction. This study applied personality to implement the natural feedback of conversational agents referring to the concept of affective computing. Two types of feedback were used to express conversational agents' personality: (1) visual feedback and (2) verbal cues. For visual feedback, participants (N = 45) watched visual feedback with different colors and motions. For verbal cues, participants (N = 60) heard different conditions of agents' voices with different scripts. The results indicated that the motions of visual feedback were more significant than colors. Fast motions could express distinct and positive personalities. Different verbal cues were perceived as different personalities. The perceptions of personalities differed according to the vocal gender. This study provided design implications for personality expressions applicable to diverse interfaces.