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Bernstein-Gruppe Components of cognition: small networks to flexible rules: Multi-modal emotion recognition and blind source separation
Projektbearbeiter:
Bogdan Vlasenko, Martin Schafföner
Finanzierung:
Bund;
The immediate goal is to analyze concurrent speech utterances and facial expressions in terms of speaker emotion and intention. Speech and face information will be combined to a multi-modal feature vector and subjected to blind source separation (ICA) analysis. In a different context similar methods were already suggested by the applicant in his Habilitationsschrift [Michaelis 80]. In the longer term, the proposed project is aimed at the automatic recognition of subtly different human interactions (e.g., friendly/cooperative, impatient/evasive, aversive/violent). A second long-term goal is to apply the automatic recognition of emotion states to a neurobiological investigation of the neural basis of emotion. A correlation with results of EEG and MRI investigations can be carried out [Heinzel 05]. The software tools to be developed here would be invaluable in brain imaging (fMRI) of human emotion.

Schlagworte

Multi-modal emotion recognition and blind source separation
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