Time for laughter
نویسندگان
چکیده
منابع مشابه
Optimized Time Series Filters for Detecting Laughter and Filler Events
Social signal detection, that is, the task of identifying vocalizations like laughter and filler events is a popular task within computational paralinguistics. Recent studies have shown that besides applying state-of-the-art machine learning methods, it is worth making use of the contextual information and adjusting the frame-level scores based on the local neighbourhood. In this study we apply...
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Each of the previous three articles in this series has examined one of the three main traditions of humour theory; those based around incongruity, superiority and the release of energy. We have seen that each of these theoretical traditions sheds some light upon humour and laughter, but also that all fail in their overly ambitious task of offering a fully comprehensive theory. This has not dete...
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This article examines re search evidence for the popu lar idea that humor and laughter have beneficial ef fects on physical health. Poten tial theoretical mechanisms for such effects are discussed first. Empirical evidence for benefi cial effects of humor and laughter on immunity, pain tolerance, blood pressure, lon gevity, and illness symptoms is then summarized. Overall, the evidence for heal...
متن کاملFusion for Audio-Visual Laughter Detection
Laughter is a highly variable signal, and can express a spectrum of emotions. This makes the automatic detection of laughter a challenging but interesting task. We perform automatic laughter detection using audio-visual data from the AMI Meeting Corpus. Audio-visual laughter detection is performed by combining (fusing) the results of a separate audio and video classifier on the decision level. ...
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In this paper, we present the detailed phonetic annotation of the publicly available AVLaughterCycle database, which can readily be used for automatic laughter processing (analysis, classification, browsing, synthesis, etc.). The phonetic annotation is used here to analyze the database, as a first step. Unsurprisingly, we find that h-like phones and central vowels are the most frequent sounds i...
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ژورنال
عنوان ژورنال: Knowledge-Based Systems
سال: 2014
ISSN: 0950-7051
DOI: 10.1016/j.knosys.2014.04.031