Implicit User-centric Personality Recognition Based on Physiological Responses to Emotional Videos

Proceedings of the 2015 ACM on International Conference on Multimodal Interaction Pub Date : 2015-11-09 DOI:10.1145/2818346.2820736

Julia Wache, Subramanian Ramanathan, M. K. Abadi, R. Vieriu, N. Sebe, Stefan Winkler

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引用次数: 16

Abstract

We present a novel framework for recognizing personality traits based on users' physiological responses to affective movie clips. Extending studies that have correlated explicit/implicit affective user responses with Extraversion and Neuroticism traits, we perform single-trial recognition of the big-five traits from Electrocardiogram (ECG), Galvanic Skin Response (GSR), Electroencephalogram (EEG) and facial emotional responses compiled from 36 users using off-the-shelf sensors. Firstly, we examine relationships among personality scales and (explicit) affective user ratings acquired in the context of prior observations. Secondly, we isolate physiological correlates of personality traits. Finally, unimodal and multimodal personality recognition results are presented. Personality differences are better revealed while analyzing responses to emotionally homogeneous (e.g., high valence, high arousal) clips, and significantly above-chance recognition is achieved for all five traits.

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基于情感视频生理反应的内隐用户中心人格识别

我们提出了一个基于用户对情感电影片段的生理反应来识别人格特征的新框架。在将外显/内隐情感用户反应与外向性和神经质特征相关联的研究基础上，我们使用现成的传感器对36名用户的心电图(ECG)、皮肤电反应(GSR)、脑电图(EEG)和面部情绪反应进行了单次试验识别。首先，我们研究了在先前观察的背景下获得的人格量表和(明确的)情感用户评级之间的关系。其次，我们分离出人格特质的生理关联。最后给出了单模态和多模态人格识别结果。在分析对情感同质(例如，高效价、高唤醒)片段的反应时，人格差异得到了更好的揭示，并且对所有五个特征的识别都显著高于机会。

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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Proceedings of the 2015 ACM on International Conference on Multimodal Interaction

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