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Increasing the credibility of anthropomorphic computer characters: The effects of manipulating nonverbal interaction style and demographic embodiment.

机译:提高拟人化计算机字符的可信度:操纵非语言交互方式和人口统计特征的影响。

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The present study examined the efficacy of enhancing human-agent interaction through the use of nonverbal behaviors. A taxonomy was created, which organizes nonverbal behaviors into functional categories, including adaptors, regulators, affect displays, illustrators, and emblems. The taxonomy further divided these behaviors by the manner in which they can be embodied (i.e., through gesture, posture, paralanguage, eye contact and facial expression). The influences of demographic variables (i.e., ethnicity, age and gender) and physical appearance (i.e., bodily and facial attractiveness, clothing and artifacts) were also considered. Forty participants were presented with computer characters that varied in terms of their ethnicity, age, and gender and asked which they would prefer to cooperate with on a computer task. The results indicated that in general youthful agents of similar ethnicity were preferred but there was no clear gender preference. In the main empirical study anthropomorphic computer characters were endowed with different levels of nonverbal behavior known to engender a trusting persona. The first level provided facial expressions, eye contact, and paralanguage. The second level added to these behaviors bodily gestures and posture. A third embodiment engendered an agent with non-trusting behaviors. Based on the results of the pilot study, the characters were youthful and selected to match each participant's ethnicity, while the gender of the agent was left open to participant's choice. It was hypothesized that those agents with the first level of nonverbal behaviors would be perceived as more credible than an anthropomorphic computer character without such attributes. Adding the second level of nonverbal behaviors was expected to result in further gains, while the non-trusting agent embodiment was suggested to be ineffective. A between subjects experimental design was used, in which forty-eight female participants interacted with one of the four computer characters that assisted them in sorting photographs. The results indicated that participants that interacted with computer characters endowed with facial expressions, eye contact, and paralanguage perceived these characters as being more trustworthy and satisfying to interact with than those who interacted with an anthropomorphic character with no nonverbal behaviors. (Abstract shortened by UMI.)
机译:本研究检查了通过使用非语言行为来增强人与人互动的功效。创建了一个分类法,该分类法将非语言行为组织为功能类别,包括适配器,调节器,影响显示,插图画家和标志。分类法将这些行为进一步划分为可体现的行为方式(即,通过手势,姿势,副语言,眼神交流和面部表情)。还考虑了人口统计学变量(即种族,年龄和性别)和外观(即身体和面部的吸引力,衣服和手工艺品)的影响。向40位参与者展示了根据种族,年龄和性别而变化的计算机角色,并询问他们希望在计算机任务上与哪些人合作。结果表明,一般来说,相似种族的年轻探员是首选,但没有明显的性别偏好。在主要的实证研究中,拟人化的计算机角色被赋予了不同程度的非语言行为,这些行为可引起信任角色。第一阶段提供面部表情,眼神交流和副语言。第二级添加到这些行为上,包括身体的手势和姿势。第三实施例使代理具有非信任行为。根据试点研究的结果,角色很年轻,可以根据每个参与者的种族进行选择,而特工的性别则留给参与者选择。有人假设,具有第一类非语言行为的主体比没有这种属性的拟人化计算机角色更可信。预计添加第二级非语言行为会带来进一步的收益,而非信任代理的实施例则被认为是无效的。使用受试者之间的实验设计,其中48位女性参与者与协助他们对照片进行分类的四个计算机角色之一进行了交互。结果表明,与具有面部表情,眼神交流和副语言的计算机角色进行交互的参与者认为,与那些与没有拟态行为的拟人角色进行交互的参与者相比,这些角色更值得信赖和与之互动。 (摘要由UMI缩短。)

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