Abstract
Combining information from multiple sources is a vivid field of research. The problem of emotion recognition is inherently multi-modal. As automatic recognition of the emotional states is performed imperfectly by the single mode classifiers, its combination is crucial. In this work, the AVEC 2011 corpus is used to evaluate several machine learning techniques in the context of information fusion. In particular temporal integration of intermediate results combined with a reject option based on classifier confidences. The results for the modes are combined using a Markov random field that is designed to be able to tackle failures of individual channels.
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Schels, M., Glodek, M., Schwenker, F., Palm, G. (2013). Revisiting AVEC 2011 – An Information Fusion Architecture. In: Apolloni, B., Bassis, S., Esposito, A., Morabito, F. (eds) Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35467-0_38
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DOI: https://doi.org/10.1007/978-3-642-35467-0_38
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