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Using immersion and information visualization to analyze human-virtual human interactions.

机译:使用沉浸式和信息可视化来分析人与人之间的互动。

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摘要

We identify verbal and nonverbal communication as the primary way in which humans try to interact with virtual human interfaces, and then use this result to develop three different approaches for analyzing interactions between humans and virtual humans. Each of these approaches is applied to analyzing interactions with virtual humans for training domain-specific interpersonal skills. In providing new approaches to analyzing virtual humans interfaces, we advance the state-of-the-art in facilitating and training interpersonal interactions with virtual human interfaces.;Verbal and nonverbal communication is identified as the primary way users try to interact with virtual humans by comparing interactions with virtual humans to similar interactions with real humans. In two user studies (n=82), participants elicited the same information from a virtual and real human using verbal communication. However, participant nonverbal behavior indicated participants were less engaged, insincere, and demonstrated a poorer attitude towards the virtual human. These behavioral differences likely stemmed from the participants' difficulty understanding the virtual humans limited expressive behavior.;The Interpersonal Scenario Visualizer (IPSViz) was then developed to enable review, analysis, and evaluation of the communication between a human and a virtual human. IPSViz generates visualizations of a human-virtual human interaction by capturing, logging, and processing the human and virtual human's verbal and nonverbal behavior. A user study (n=27) shows that conducting an interaction with a virtual human and then reviewing that interaction with IPSViz elicits self-reflection on interpersonal skills, including verbal and nonverbal behavior, rapport-building, and communicating clearly under stress.;The next system, the Virtual Social Perspective-taking (VSP) system, enables review, analysis, and evaluation of an interaction with a virtual human from the perspective of the virtual human. The VSP system records a virtual human patients experience of talking to a medical student, and then uses the recording to transport the medical student into the patients body and relive the conversation through her eyes. The student relives the conversation to better understand the virtual human patients perspective and learn to address her and future real patients - fears. The results of a pilot study (n = 16) indicate that VSP encourages reflection on the perspectives of others and elicits self-directed change of behavior in future social interactions.;The last system, IPSVizN, enables review, analysis, and evaluation of trends and outliers in human-virtual human interactions. IPSVizN processes groups of human-virtual human interaction logs to generate summary visualizations of the interactions. An evaluation of IPSVizN with representative end-users found that participants were able to rapidly (within minutes) identify trends and outliers in overall group interpersonal skills, including verbal behavior, organization, completeness, empathy, and communicating under stress. Identifying these trends and outliers without IPSVizN would have required hours of manual effort.
机译:我们将口头和非语言交流确定为人类尝试与虚拟人机界面交互的主要方式,然后使用此结果来开发三种不同的方法来分析人类与虚拟人机之间的交互。这些方法均适用于分析与虚拟人的互动,以训练特定领域的人际交往能力。在提供分析虚拟人机界面的新方法时,我们在促进和培训与虚拟人机界面的人际互动方面发展了最新技术。言语和非语言交流被认为是用户尝试通过以下方式与虚拟人机交互的主要方式比较与虚拟人的互动与与真实人的类似互动。在两项用户研究(n = 82)中,参与者使用口头交流从虚拟的和真实的人身上得到了相同的信息。但是,参与者的非语言行为表明参与者的参与度较低,不真诚,并且对虚拟人的态度较差。这些行为差异可能是由于参与者难以理解虚拟人有限的表达行为而引起的。然后开发了人际关系场景可视化工具(IPSViz)来检查,分析和评估人与虚拟人之间的交流。 IPSViz通过捕获,记录和处理人与虚拟人的言语和非言语行为,生成人与虚拟人互动的可视化效果。一项用户研究(n = 27)显示,与虚拟人进行互动,然后查看与IPSViz的互动会引起对人际交往能力的自我反思,包括言语和非言语行为,融洽的建立以及在压力下的清晰沟通。下一个系统,即虚拟社会观点收集(VSP)系统,可以从虚拟人的角度审查,分析和评估与虚拟人的交互。 VSP系统记录了虚拟的人类患者与医科学生交谈的经历,然后使用该记录将医科学生运送到患者体内,并通过她的眼睛重现对话。学生可以重新进行对话,以更好地了解虚拟人类患者的观点,并学会解决她和未来的真实患者-恐惧。一项初步研究的结果(n = 16)表明,VSP鼓励反思他人的观点,并引发未来社会互动中行为的自我指导改变。最后一个系统IPSVizN可以对趋势进行审阅,分析和评估和人与人之间互动的异常点。 IPSVizN处理人与虚拟人的交互日志组,以生成交互的摘要可视化。通过对具有代表性的最终用户进行的IPSVizN评估,发现参与者能够(在几分钟之内)快速识别总体人际交往能力的趋势和异常值,包括言语行为,组织,完整性,同情心和在压力下进行交流。要在没有IPSVizN的情况下识别这些趋势和异常值,将需要花费大量的人工。

著录项

  • 作者

    Raij, Andrew Brian.;

  • 作者单位

    University of Florida.;

  • 授予单位 University of Florida.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 206 p.
  • 总页数 206
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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