Cross-Cultural Production and Detection of Deception from Speech

Sarah Ita Levitan, Guozhen An, Mandi Wang, Gideon Mendels, Julia Hirschberg, Michelle Levine, A. Rosenberg
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引用次数: 51

Abstract

Detecting deception from different dimensions of human behavior has been a major goal of research in psychology and computational linguistics for some years and is currently of considerable interest to military and law enforcement agencies. However, relatively little work has been done to develop automatic methods to detect deception from spoken language or to compare deception detection and production between different cultures. We present results of experiments on a new corpus of deceptive and non-deceptive speech, collected from native speakers of Standard American English and Mandarin Chinese, all speaking English, to investigate acoustic, prosodic, and lexical cues to deception. We report first on the role of personality factors derived from the NEO-FFI (Neuroticism-Extraversion-Openness Five Factor Inventory) and of gender, ethnicity and confidence ratings on subjects? ability to deceive and to detect deception. We then present classification results discriminating deceptive from non-deceptive speech, using these features as well as acoustic and prosodic cues. We find that combining acoustic and prosodic features with information about the speaker?s personality, gender, and language results in a classification accuracy of 65.86%, which represents ~10% relative improvement from baseline accuracy.
言语欺骗的跨文化产生和检测
多年来,从人类行为的不同维度检测欺骗一直是心理学和计算语言学研究的一个主要目标,目前也引起了军事和执法机构的极大兴趣。然而,在开发从口语中检测欺骗的自动方法或比较不同文化之间的欺骗检测和产生方面,所做的工作相对较少。我们介绍了一个新的欺骗性和非欺骗性言语语料库的实验结果,这些语料库收集了母语为标准美式英语和普通话的人,他们都说英语,以研究欺骗的声学、韵律和词汇线索。我们首先报告了NEO-FFI(神经质-外向性-开放性五因素量表)中人格因素的作用,以及受试者的性别、种族和信心评级。欺骗和识破欺骗的能力。然后,我们展示了使用这些特征以及声学和韵律线索区分欺骗性和非欺骗性语音的分类结果。我们发现,将声学和韵律特征与说话人的信息结合起来,S的个性、性别和语言的分类准确率为65.86%,比基线准确率相对提高了约10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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