This paper presents the large audiovisual laughter database recorded as part of the AVLaughterCycle project held during the eNTER-FACE'09 Workshop in Genova. 24 subjects participated. The freely available database includes audio signal and video recordings as well as facial motion tracking, thanks to markers placed on the subjects' face. Annotations of the recordings, focusing on laughter description, are also provided and exhibited in this paper. In total, the corpus contains more than 1000 spontaneous laughs and 27 acted laughs. The laughter utterances are highly variable: the laughter duration ranges from 250ms to 82s and the sounds cover voiced vowels, breath-like expirations, hum-, hiccup- or grunt-like sounds, etc. However, as the subjects had no one to interact with, the database contains very few speech-laughs. Acted laughs tend to be longer than spontaneous ones and are more often composed of voiced vowels. The database can be useful for automatic laughter processing or cognitive science works. For the AVLaughterCycle project, it has served to animate a laughing virtual agent with an output laugh linked to the conversational partner's input laugh.

The AVLaughterCycle database

Niewiadomski R.;
2010-01-01

Abstract

This paper presents the large audiovisual laughter database recorded as part of the AVLaughterCycle project held during the eNTER-FACE'09 Workshop in Genova. 24 subjects participated. The freely available database includes audio signal and video recordings as well as facial motion tracking, thanks to markers placed on the subjects' face. Annotations of the recordings, focusing on laughter description, are also provided and exhibited in this paper. In total, the corpus contains more than 1000 spontaneous laughs and 27 acted laughs. The laughter utterances are highly variable: the laughter duration ranges from 250ms to 82s and the sounds cover voiced vowels, breath-like expirations, hum-, hiccup- or grunt-like sounds, etc. However, as the subjects had no one to interact with, the database contains very few speech-laughs. Acted laughs tend to be longer than spontaneous ones and are more often composed of voiced vowels. The database can be useful for automatic laughter processing or cognitive science works. For the AVLaughterCycle project, it has served to animate a laughing virtual agent with an output laugh linked to the conversational partner's input laugh.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1124258
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