Expressing Personalities of Conversational Agents through Visual and Verbal Feedback

Abstract

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. amplitudes and speeds of gestures and movements. Extroverts demonstrate faster, wider, and broader movements than introverts [4]. In addition, extroverts tend to demonstrate more reactive and faster movements and body gestures than introverts [5]. Personality and verbal traits are also highly interrelated. Extroverts tend to express more emotionality with positive emotions and use fewer formal expressions with agreement and gratitude [6]. Extroverts also demonstrate shorter silences and use more positive words and informal expressions than introverts. Introverts use more abstract words and formal words than extroverts [2,7].Gestures are difficult to implement with current conversational agents because most of them are designed in the form of AI speakers. Existing conversational agents in the current market, including Amazon Alexa and Google Home, are not able to implement gesture movements. Instead of using gestures, AI speakers deliver simple visual feedback through a smart display in response to voice commands. Considering the current form of conversational agents, visual feedback was chosen as the personality expression element. As people with different personalities demonstrate different gesture speeds, the lighting speed could also be perceived as different personalities. Quick lighting is perceived as more active than slow lighting; therefore, the study posits the following research question: RQ 1. Can different visual feedback be perceived as different personalities?Most current AI speakers use a consistent voice with the same speech style. As extroverts and introverts demonstrate different verbal traits, different verbal traits are perceived as different personalities. Therefore, the study posits the second research question: RQ 2. Can different verbal cues be perceived as different personalities?Unlike previous studies, the current study applied a wider range of personalities rather than focusing on expressing only two contrasting persona...

Open Innovation Engineering—Preliminary Study on New Entrance of Technology to Market

“…The first study showed that, as the uses of conversational agents increase, the affective and social abilities of agents become as important as their functional abilities in the open innovation engineering channel and system dynamics approaches [55]. Consequently, by building networks to harness innovation synergies, open system approaches can motivate sustainable development and creative collaboration based on both online and offline learning systems [56,57].…”

A Survey of Automatic Personality Detection from Texts

“…People are more engaged in interacting with others who have similar personality profiles as it requires less information processing and cognitive load (Wu et al, 2017). This idea has been used in designing dialog systems and personal assistants emphasising the need for them to be able to detect and mimic the personality style of a user (Cassell and Bickmore, 2003;Ma et al, 2019;Seo-young Lee and Lee, 2019), in order to behave similarly to humans that instinctively adapt to the other person's personality (Funder and Sneed, 1993;McLarney-Vesotski et al, 2006). It has been shown that adding personality traits to virtual agents leads to significantly better perceived emotional intelligence of such systems (Ma et al, 2019).…”

A Framework of Personality Cues for Conversational Agents

“…Also, disfluency in speech and fillers [46] portray a less conscientious CA. Slow speed and high emotionality [47] in voice are found to have a correlation with high conscientiousness -however, this only applies to the female voice [47].…”

“…Databases: Scopus ACM Digital Library controlled body movements [22] reflect a high score in openness when it comes to an ECA's body language, the studies did not contain any further information on the trait's opposite pole. In the category paraverbal language, research showed that disfluencies in speech [46] is characteristic for low openness, while high emotionality in female voice [47] is considered a personality cue for high openness. We did not find any cues regarding verbal language.…”

“…For paraverbal language, a higher proportion of silence to speech and the presence of speech discontinuities [16] reflects high neuroticism. Furthermore, a male voice that speaks fast and has a low wordiness [47] has as well been linked to low emotional stability in behavior. As for the category body language, a number of cues have been associated with high neuroticism: fewer other-directed gestures and more self-directed gestures, more frequent shifts in posture such as leaning more forward or a more tense and stiff posture [23], as well as more non-signaling hand motions (e.g.…”