Laughter in Conversation: Features of Occurrence and Acoustic Structure

Vettin, Julia; Todt, Dietmar

doi:10.1023/b:jonb.0000023654.73558.72

Cited by 136 publications

(138 citation statements)

References 36 publications

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“…Laughter is a largely stereotyped vocalization, explaining its highly identifiable sound (Provine & Yong, 1991), but the sound characteristics are quite variable within and between individuals, and within social contexts (Bachorowski, Smoski, & Owren, 2001;Vettin & Todt, 2004). Few studies have directly examined relationships between specific acoustic properties and perceptual judgments.…”

Section: Introductionmentioning

confidence: 99%

The animal nature of spontaneous human laughter

Bryant

Aktipis

2014

Evolution and Human Behavior

176

185

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Section: Introductionmentioning

confidence: 99%

The animal nature of spontaneous human laughter

Bryant

Aktipis

2014

Evolution and Human Behavior

176

185

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“…Laughter is a powerful affective and social signal since people very often express their emotion and regulate conversations by laughing. It has been reported that people frequently laugh after their own utterances and it has been suggested that this provides a mechanism to change the meaning of the utterance [63].…”

Section: Introductionmentioning

confidence: 99%

Audiovisual Discrimination Between Speech and Laughter: Why and When Visual Information Might Help

Petridis

Pantić

2011

IEEE Trans. Multimedia

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Abstract-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 and head pose for video and cepstral and prosodic features for audio. Two types of experiments were performed: 1) subject-independent cross-validation on the AMI dataset and 2) cross-database experiments on the AMI and SAL datasets. We experimented with different combinations of cues with the most informative being the combination of facial expressions, cepstral, and prosodic features. Our results suggest that the performance of the audiovisual approach is better on average than single-modal approaches. The addition of visual information produces better results when it comes to female subjects. When the training conditions are less diverse in terms of head movements than the testing conditions (training on the SAL dataset, testing on the AMI dataset), then no improvement was observed with the addition of visual information. On the other hand, when the training conditions are similar (cross validation on the AMI dataset), or more diverse (training on the AMI dataset, testing on the SAL dataset), in terms of head movements than is the case in the testing conditions, an absolute increase of about 3% in the F1 rate for laughter is reported when visual information is added to audio information.Index Terms-Human behavior analysis, laughter-versusspeech discrimination, neural networks, principal components analysis (PCA).

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“…Such deep structure must exist or we could not reliably identify a vocalization as laughter-and laughter is certainly recognizable, as the only positive vocal emotional expression identified across culturally and geographically distinct groups (Sauter, Eisner, Ekman, & Scott, 2010). Other research has confirmed laughter's harmonic and temporal structure and context specificity Bachorowski, Smoski, & Owren, 2001;Scott, 2013;Smoski & Bachorowski, 2003;Vettin & Todt, 2004).…”

Section: Laughter Structurementioning

confidence: 97%

Laughter as an approach to vocal evolution: The bipedal theory

Provine

2016

Psychon Bull Rev

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Laughter is a simple, stereotyped, innate, human play vocalization that is ideal for the study of vocal evolution. The basic approach of describing the act of laughter and when we do it has revealed a variety of phenomena of social, linguistic, and neurological significance. Findings include the acoustic structure of laughter, the minimal voluntary control of laughter, the punctuation effect (which describes the placement of laughter in conversation and indicates the dominance of speech over laughter), and the role of laughter in human matching and mating. Especially notable is the use of laughter to discover why humans can speak and other apes cannot. Quadrupeds, including our primate ancestors, have a 1:1 relation between breathing and stride because their thorax must absorb forelimb impacts during running. The direct link between breathing and locomotion limits vocalizations to short, simple utterances, such as the characteristic panting chimpanzee laugh (one sound per inward or outward breath). The evolution of bipedal locomotion freed the respiration system of its support function during running, permitting greater breath control and the selection for humantype laughter (a parsed exhalation), and subsequently the virtuosic, sustained, expiratory vocalization of speech. This is the basis of the bipedal theory of speech evolution.

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Laughter in Conversation: Features of Occurrence and Acoustic Structure

Cited by 136 publications

References 36 publications

The animal nature of spontaneous human laughter

The animal nature of spontaneous human laughter

Audiovisual Discrimination Between Speech and Laughter: Why and When Visual Information Might Help

Laughter as an approach to vocal evolution: The bipedal theory

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