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The paper describes BIRAFFE2 data set, which is a result of an affectivecomputing experiment conducted between 2019 and 2020, that aimed to developcomputer models for classification and recognition of emotion. Such work isimportant to develop new methods of natural Human-AI interaction. As we believethat models of emotion should be personalized by design, we present an unifiedparadigm allowing to capture emotional responses of different persons, takingindividual personality differences into account. We combine classicalpsychological paradigms of emotional response collection with the newerapproach, based on the observation of the computer game player. By capturingones psycho-physiological reactions (ECG, EDA signal recording), mimicexpressions (facial emotion recognition), subjective valence-arousal balanceratings (widget ratings) and gameplay progression (accelerometer and screencastrecording), we provide a framework that can be easily used and developed forthe purpose of the machine learning methods.

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