Steffen Walter

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Cognitive-technical intelligence is envisioned to be constantly available and capable of adapting to the user's emotions. However, the question is: what specific emotions should be reliably recognised by intelligent systems? Hence, in this study, we have attempted to identify similarities and differences of emotions between human-human (HHI) and(More)
The objective measurement of subjective, multidimensionally experienced pain is still a problem that has yet to be adequately solved. Though verbal methods (i.e., pain scales, questionnaires) and visual analogue scales are commonly used for measuring clinical pain, they tend to lack in reliability or validity when applied to mentally impaired individuals.(More)
Recent affective computing findings indicated that effectively identifying users’ emotional responses is an important issue to improve the quality of ambient intelligence. In the current study, two bipolar facial electromyography (EMG) channels over corrugator supercilii and zygomaticus major were employed for differentiating various emotional states in two(More)
Pain is what the patient says it is. But what about these who cannot utter? Automatic pain monitoring opens up prospects for better treatment, but accurate assessment of pain is challenging due to the subjective nature of pain. To facilitate advances, we contribute a new dataset, the BioVid Heat Pain Database which contains videos and physiological data of(More)
The goal of automatic biopsychological emotion recognition of companion technologies is to ensure reliable and valid classification rates. In this paper, emotional states were induced via a Wizard-of-Oz mental trainer scenario, which is based on the valence–arousal–dominance model. In most experiments, classification algorithms are tested via leave-out(More)
The goal of our research is the development of algorithms for automatic estimation of a person’s verbal intelligence based on the analysis of transcribed spoken utterances. In this paper we present the corpus of German native speakers’ monologues and dialogues about the same topics collected at the University of Ulm, Germany. The monologues were(More)
Philipp Werner1 Ayoub Al-Hamadi1 Robert Niese1 Steffen Walter2 Sascha Gruss2 Harald C. Traue2 1 Institute for Information Technology and Communications, Otto-von-Guericke University, Magdeburg, Germany 2 Department(More)
The individual nature of physiological measurements of human affective states makes it very difficult to transfer statistical classifiers from one subject to another. In this work, we propose an approach to incorporate unlabeled data into a supervised classifier training in order to conduct an emotion classification. The key idea of the method is to conduct(More)