This paper is about automated labeling of emotions. Prototypes have been developed for extraction of features from facial expressions and speech. To train such systems data is needed. In this paper we report about the recordings of semi-spontaneous emotions. Multimodal emotional reactions are evoked in 21 controlled contexts. The purpose of this database is to make it a benchmark for the current and future emotion recognition studies in order to compare the results from different research groups. Validation of the recorded data is done online. Over 60 users scored the apex images (1.272 ratings), audio clips (201 ratings) and video clips (503 ratings) on the valence and arousal scale. Textual validation is done based on Whissell’s Dictionary of Affect in Language. A comparison is made between the scores of all four validation methods and the results showed some clusters for distinct emotions.
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