Drimalla, H., Baskow, I., Behnia, B., Röpke, S. and Dziobek, I. (2019) Imitation and Recognition of Facial Emotions in Autism – A Computer Vision Approach.
The Berlin Emotion Recognition Test (BERT) is a computer-based task for sensitively assessing emotion recognition. The BERT consists of a total of 48 photographs of facial expressions of professional actors displaying one of the six basic emotions (; for stimulus production see ). The face is centred in front of a dark grey background. There are eight pictures per emotion, and each is expressed by four different female and four different male actors. Below each picture, two emotional words are presented, and the participant is asked how the person is feeling. Only one of the two possible options correctly describes the emotion expressed. The emotion recognition score is the percentage of correct answers. The position of the correct answer, as well as the order of the picture, is randomized.
To develop a sensitive task, the pictures were extracted from video clips in which professional actors expressed the target emotions. The actors had been instructed with emotional scripts (e.g. imagine you receive an unexpected present) to perform the facial expressions, starting with a neutral expression. This led to a more naturalistic material. From each video clip, frames of three different intensities were extracted. These pictures of facial emotion expressions built the item pool for the BERT. This pool was reduced to the most sensitive items in a pre-study at an open house public event in Berlin, Germany, where large scientific institutions open their doors for the general public. In this pre-study with a sample of opportunity, 46 participants were asked to recognize the emotion of each of the items. Each picture was presented with the six basic emotions as possible answers. Based on their responses, for each video clip, we selected the picture, which discriminated best between low- and high-scoring participants. Additionally, we identified for each item the most difficult distractor out of the five incorrect emotion labels. In a follow-up online-study  with 436 participants, the selected pictures and distractors were tested and further improved with respect to reliability and discriminatory power by choosing the best eight items per emotion and most-difficult distractor.
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 Drimalla H, Kirst S, Dziobek I. Insights about Emotion Recognition by BERT and ERNIE (two new psychological tests) Manuscript in preparation.