arXiv 2007.150482020-07cs.HCcs.AIcs.LG

BIRAFFE2实验。AI系统中生物反应和面孔的识别个性化研究

The BIRAFFE2 Experiment. Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems

Jagiellonian University（雅盖隆大学）；AGH University of Science and Technology（AGH科技大学）

Krzysztof Kutt, Dominika Drążyk, Maciej Szelążek, Szymon Bobek, Grzegorz J. Nalepa

备注：: Presented during the Human-AI Interaction Workshop at ECAI 2020; Acknowledgements added

摘要：

本文描述了BIRAFFE2数据集，这是2019年至2020年期间进行的情感计算实验的结果，旨在开发用于情感分类和识别的计算机模型。这项工作对于开发自然的人机交互的新方法非常重要。由于我们认为情感模型应该通过设计进行个性化，因此我们提出了一个统一的范式，可以捕捉不同人的情感反应，同时考虑到个体的个性差异。我们结合了经典的心理学范式的情绪反应收集与新的方法，根据观察的计算机游戏玩家。通过捕捉一个人的心理生理反应（ECG，EDA信号记录），模仿表情（面部情绪识别），主观效价唤醒平衡评级（小部件评级）和游戏进程（加速度计和截屏记录），我们提供了一个框架，可以很容易地使用和开发的目的机器学习方法。

英文摘要：

The paper describes BIRAFFE2 data set, which is a result of an affective computing experiment conducted between 2019 and 2020, that aimed to develop computer models for classification and recognition of emotion. Such work is important to develop new methods of natural Human-AI interaction. As we believe that models of emotion should be personalized by design, we present an unified paradigm allowing to capture emotional responses of different persons, taking individual personality differences into account. We combine classical psychological paradigms of emotional response collection with the newer approach, based on the observation of the computer game player. By capturing ones psycho-physiological reactions (ECG, EDA signal recording), mimic expressions (facial emotion recognition), subjective valence-arousal balance ratings (widget ratings) and gameplay progression (accelerometer and screencast recording), we provide a framework that can be easily used and developed for the purpose of the machine learning methods.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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英文摘要：

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