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Multimodal Behavior Processing > Research

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The research group Multimodal Behavior Processing, headed by Jun.-Prof. Dr. Hanna Drimalla, is dedicated to the automatic analysis of social interaction signals (e.g., facial expression, gaze behavior, voice etc.) using machine learning as well as speech and image processing. Three aspects are the focus of our research: the detection of positive and negative affect, the measurement of stress, and the analysis of social interaction patterns. All three have in common that they are multimodal and time-dependent phenomena. To address this complexity, we collect innovative training data and develop novel analysis methods. Our goal is Empathic Artificial Intelligence, that recognizes and adapts to a user's mental state.

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