从对话中识别性别、种族和个性的个体差异用于欺骗检测

Proceedings of the Second Workshop on Computational Approaches to Deception Detection Pub Date : 1900-01-01 DOI:10.18653/v1/W16-0806

Sarah Ita Levitan, Yocheved Levitan, Guozhen An, Michelle Levine, Rivka Levitan, A. Rosenberg, Julia Hirschberg

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引用次数: 23

摘要

当自动检测欺骗时，重要的是模拟说话者之间的个体差异。我们探索了个体特征的自动识别，如性别、母语和个性，使用声学-韵律和词汇特征，从最初的非欺骗性对话。我们还探讨了使用相同的特征来预测欺骗和欺骗检测的成功。

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Identifying Individual Differences in Gender, Ethnicity, and Personality from Dialogue for Deception Detection

When automatically detecting deception, it is important to model individual differences across speakers. We explore the automatic identification of individual traits such as gender, native language, and personality, using acoustic-prosodic and lexical features from an initial non-deceptive dialogue. We also explore predicting success at deception and at deception detection, using the same features.

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Proceedings of the Second Workshop on Computational Approaches to Deception Detection

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