Quantitative Laughter Detection, Measurement, and Classification - A Critical Survey

研究成果: Article査読

17 被引用数 (Scopus)

抄録

The study of human nonverbal social behaviors has taken a more quantitative and computational approach in recent years due to the development of smart interfaces and virtual agents or robots able to interact socially. One of the most interesting nonverbal social behaviors, producing a characteristic vocal signal, is laughing. Laughter is produced in several different situations: in response to external physical, cognitive, or emotional stimuli; to negotiate social interactions; and also, pathologically, as a consequence of neural damage. For this reason, laughter has attracted researchers from many disciplines. A consequence of this multidisciplinarity is the absence of a holistic vision of this complex behavior: the methods of analysis and classification of laughter, as well as the terminology used, are heterogeneous; the findings sometimes contradictory and poorly documented. This survey aims at collecting and presenting objective measurement methods and results from a variety of different studies in different fields, to contribute to build a unified model and taxonomy of laughter. This could be successfully used for advances in several fields, from artificial intelligence and human-robot interaction to medicine and psychiatry.

本文言語English
論文番号7403873
ページ(範囲)148-162
ページ数15
ジャーナルIEEE Reviews in Biomedical Engineering
9
DOI
出版ステータスPublished - 2016

ASJC Scopus subject areas

  • 生体医工学

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