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首页> 外文学位 >Decision support for rapid assessment of truth and deception using automated assessment technologies and kiosk-based embodied conversational agents.
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Decision support for rapid assessment of truth and deception using automated assessment technologies and kiosk-based embodied conversational agents.

机译：使用自动评估技术和基于信息亭的具体对话代理，为快速评估真相和欺骗提供决策支持。

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摘要

A pressing need exists for effective decision support systems to facilitate the rapid and accurate screening of large volumes of people. Millions of travelers transit through international borders and secure areas on an annual basis. Humans are exceptionally poor at detecting lying and deception and perform, on average, no better than chance. This research study focuses on the development, design and implementation of a Kiosk for Rapid Assessment of Deception (K-RAD) that integrates questioning with response processing and deception detection. An exploratory pilot study (N=68) and a primary study (N=225) were executed.;The K-RAD was designed to have a three-dimensional figure, an "Embodied Conversational Agent" (ECA), deliver the questions through speech. This delivery mechanism was chosen because human subjects have been shown in the past to react emotionally to ECAs during conversational interactions, and emotional arousal is one of the cues to deception. Responses were analyzed for deception cues, focusing on kinesic, linguistic, and vocalic characteristics that can be captured for automated processing and which would be unique to this setting.;The results show unique subject behaviors. Subjects exhibited minimal movement and had very little tendency to change posture. Some subjects (6%) referred to the ECA as an authority figure, using "sir" when responding. Subjects positioned themselves at varying distances from the ECA, with significant gender differences. Post-experiment surveys indicated a gender difference in overall stress, with female subjects reporting significantly higher levels, independent of the experimental condition.;Postural-based logistic regression created significant classification models for the pilot (59.1% classification accuracy) and primary (57.2% & 62.8% classification accuracies) studies. Movement analysis had varying and conflicting results. A robust deception index with a 68.1% classification accuracy was achievable in the pilot study based on high-frequency movement and arm placement. Primary study deception indices were not significant.;The results include a comprehensive set of observations and lessons learned regarding kiosk design, deception technologies, detection effectiveness, and future considerations to take into account when creating a next-generation K-RAD system. Many challenges remain, but the concept is functional, promising, and could revolutionize security screening and deception detection in a variety of settings.
机译：迫切需要有效的决策支持系统来促进对大量人员的快速准确筛查。每年有数百万的旅客经过国际边界和安全地区。人类在检测撒谎和欺骗方面非常差劲，并且平均而言，其表现不比机会好。这项研究专注于开发，设计和实施一个快速评估欺骗的信息亭（K-RAD），该信息亭将询问与响应处理和欺骗检测相结合。进行了探索性先导研究（N = 68）和初步研究（N = 225）。； K-RAD被设计为具有三维图形，即“嵌入式对话代理”（ECA），通过言语。之所以选择这种传递机制，是因为过去已经证明人类对象在对话互动过程中会对ECA产生情感反应，而情感唤醒是欺骗的线索之一。分析了响应的欺骗线索，重点是可以捕获以进行自动处理的运动，语言和声音特征，这对于该设置是唯一的。；结果显示了独特的主题行为。受试者表现出最小的运动并且几乎没有改变姿势的趋势。一些受试者（6％）将ECA作为权威人物，并在回答时使用“先生”。受试者与ECA的距离不同，性别差异也很大。实验后调查表明，总体压力存在性别差异，女性受试者报告的水平明显高于实验条件。基于姿势的逻辑回归为飞行员（59.1％的分类准确度）和初级（57.2％）建立了显着的分类模型＆62.8％的分类精度）研究。运动分析的结果各不相同且相互矛盾。在基于高频运动和手臂放置的初步研究中，可以实现分类精度为68.1％的强大欺骗指数。初步研究的欺骗指数并不显着。结果包括关于信息亭设计，欺骗技术，检测效果以及创建下一代K-RAD系统时要考虑的未来因素的全面观察和教训。仍然存在许多挑战，但是这个概念是实用的，很有前途的，并且可以在各种情况下彻底改变安全性筛选和欺骗检测。

著录项

  • 作者

    Patton, Mark W.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Business Administration General.;Information Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 314 p.
  • 总页数 314
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 贸易经济;信息与知识传播;
  • 关键词

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