Abstract
This work focuses on the detection of laughter in natural multiparty discourses. For the given task features of two different modalities are used from unobtrusive sources, namely a room microphone and a 360 degree camera. A relatively novel approach using Echo State Networks (ESN) is utilized to achieve the task at hand. Among others, a possible application is the online detection of laughter in human robot interaction in order to enable the robot to react appropriately in a timely fashion towards human communication, since laughter is an important communication utility.
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Scherer, S., Schwenker, F., Campbell, N., Palm, G. (2009). Multimodal Laughter Detection in Natural Discourses. In: Ritter, H., Sagerer, G., Dillmann, R., Buss, M. (eds) Human Centered Robot Systems. Cognitive Systems Monographs, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10403-9_12
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DOI: https://doi.org/10.1007/978-3-642-10403-9_12
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