Detecting Emotional Content from the Motion of an Orchestra Conductor
In this paper we present methods for analysis of the emotional content of human movement. We have studied orchestra conductor’s movements that portrayed different emotional states. Using signal processing tools and artificial neural networks we were able to determine the emotional state intended by the conductor. The test set included various musical contexts with different tempos, dynamics and nuances in the data set. Some context changes do not disturb the system while other changes cause severe performance losses. The system demonstrates that for some conductors the intended emotional content of these movements can be detected with our methods.
KeywordsEmotional State Confusion Matrix Emotional Content Context Change Emotional Space
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