论文标题
隐式用户行为信号的性别和情感识别
Gender and Emotion Recognition from Implicit User Behavior Signals
论文作者
论文摘要
这项工作探讨了隐性行为提示的实用性，即脑电图（EEG）信号和眼睛运动，以实现性别识别（GR）和情感识别（ER）的心理物理行为。具体而言，检查的提示是通过低成本的现成传感器获得的。 28个用户（14位男性）识别出毫无封闭（无面具）的情绪，并部分被遮住（眼睛或嘴巴掩盖）的情感面孔；他们的脑电图反应包含特定性别的差异，而他们的眼睛运动是感知到的面部情绪的特征。实验结果表明，（a）可靠的gr和er可以通过脑电图和眼睛特征来实现，（b）女性观察到负面情绪的差异认知处理，以及（c）基于眼睛的性别差异在部分面部遮挡下表现为眼部和嘴膜状况。
This work explores the utility of implicit behavioral cues, namely, Electroencephalogram (EEG) signals and eye movements for gender recognition (GR) and emotion recognition (ER) from psychophysical behavior. Specifically, the examined cues are acquired via low-cost, off-the-shelf sensors. 28 users (14 male) recognized emotions from unoccluded (no mask) and partially occluded (eye or mouth masked) emotive faces; their EEG responses contained gender-specific differences, while their eye movements were characteristic of the perceived facial emotions. Experimental results reveal that (a) reliable GR and ER is achievable with EEG and eye features, (b) differential cognitive processing of negative emotions is observed for females and (c) eye gaze-based gender differences manifest under partial face occlusion, as typified by the eye and mouth mask conditions.
