Amused speech components analysis and classification: Towards an amusement arousal level assessment system. (August 2017)

• Record Type: Journal Article
• Authors: El Haddad, Kevin; Çakmak, Hüseyin; Dupont, Stéphane; Dutoit, Thierry
• Is Part Of: Computers & electrical engineering. Volume 62(2017)
• Page Start: 588
• Page End: 600
• Publication Date: 2017-08
• Subjects: Amusement intensity level -- Laughter -- Smile -- Paralinguistic -- Affective computing -- Machine learning application; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.06.012
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: In this paper, we present our work on analysis and classification of smiled vowels, chuckling (or shaking) vowels and laughter syllables. This work is part of a larger framework that aims at assessing the level of amusement in speech using the audio modality only. Indeed all of these three categories occur in amused speech and are considered to contribute in the expression of different levels of amusement. We first analyze these three amused speech components on the acoustic level. Then, we improve a classification system we previously developed. With a limited amount of data and features, we are able to obtain good classification results with different systems. Among the compared systems, the best one achieved 82.8% of accuracy, therefore outperforming chance.