Despite its relevance for human-human communication, laughter has been quite under-investigated and under-exploited in human-machine interaction. Nevertheless, endowing machines with the capability of analyzing laughter (i.e., to detect when the user is laughing, to measure intensity of laughter, to distinguish between different laughter styles and types) in ecological contexts is a very challenging task. An approach to laughter recognition consisting of the real-time analysis of a single communication modality, i.e., body, is presented in this paper and positive results of an evaluation study are discussed.
How is your laugh today?
MANCINI, MAURIZIO;VARNI, GIOVANNA;NIEWIADOMSKI, RADOSLAW;VOLPE, GUALTIERO;CAMURRI, ANTONIO
2014-01-01
Abstract
Despite its relevance for human-human communication, laughter has been quite under-investigated and under-exploited in human-machine interaction. Nevertheless, endowing machines with the capability of analyzing laughter (i.e., to detect when the user is laughing, to measure intensity of laughter, to distinguish between different laughter styles and types) in ecological contexts is a very challenging task. An approach to laughter recognition consisting of the real-time analysis of a single communication modality, i.e., body, is presented in this paper and positive results of an evaluation study are discussed.
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