Real-time Recognition of User State with Physiological Signals

One of my research areas is physiological signal processing: the development of methods and algorithms for the automatic, on-line recognition of the affective user state on the basis of physiological measurements. Specific Topics are data acquisition, affect elicitation, data-driven and fast feature extraction, artifact recognition, user-independent classification and user adaption. The field of possible applications ranges from affect-aware user interfaces to completely new applications related to affect.

Automatic Analysis of A-Typical Speech

My current focus of research is the automatic analysis of atypical speech, such as pathologic speech, nonnative speech, or speech in certain user states (e.g. alcoholic intoxination, sleepiness, emotion). Applications range from screening, therapy control, second language tests, recognition of user states to computer-assisted training and therapy. A specific example is automatic pronuciation assessment for computer-assisted language learning (CALL). 

Projects

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Publications

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