Abstract

Laughter is a crucial signal for communication and managing interactions. Until now no consensual approach has emerged for classifying laughter. We propose a new framework for laughter analysis and classification, based on the pivotal assumption that laughter has propositional content. We propose an annotation scheme to classify the pragmatic functions of laughter taking into account the form, the laughable, the social, situational, and linguistic context. We apply the framework and taxonomy proposed in a multilingual corpus study (French, Mandarin Chinese, and English), involving a variety of situational contexts. Our results give rise to novel generalizations about the range of meanings laughter exhibits, the placement of the laughable, and how placement and arousal relate to the functions of laughter. We have tested and refuted the validity of the commonly accepted assumption that laughter directly follows its laughable. In the concluding section, we discuss the implications our work has for spoken dialogue systems. We stress that laughter integration in spoken dialogue systems is not only crucial for emotional and affective computing aspects, but also for aspects related to natural language understanding and pragmatic reasoning. We formulate the emergent computational challenges for incorporating laughter in spoken dialogue systems.

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