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Past research on automatic laughter classification/detection has focused mainly on audio-based approaches. Here we present an audiovisual approach to distinguishing laughter from speech, and we show that integrating the information from audio and video channels may lead to improved performance over single-modal approaches. Both audio and visual channels consist of two streams (cues), facial expressions...
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