Analysis of production characteristics of laughter. (March 2015)

• Record Type: Journal Article
• Authors: Mittal, Vinay Kumar; Yegnanarayana, Bayya
• Is Part Of: Computer speech & language. Volume 30(2015)
• Page Start: 99
• Page End: 115
• Publication Date: 2015-03
• Subjects: Laughter analysis -- Nonspeech-laugh -- Laughed-speech -- Modified zero-frequency filtering -- Dominant frequency -- Closed phase quotient -- EGG -- Differenced EGG; Speech processing systems -- Periodicals; Automatic speech recognition -- Periodicals; Computers -- Periodicals; Linguistics -- Periodicals; Speech-Language Pathology -- Periodicals; Traitement automatique de la parole -- Périodiques; Reconnaissance automatique de la parole -- Périodiques; Automatic speech recognition; Speech processing systems; Electronic journals; Periodicals; 006.454
• DOI: 10.1016/j.csl.2014.08.004
• Languages: English
• ISSNs: 0885-2308

Abstract

Abstract : Highlights: Production characteristics of laughter are analysed using EGG and speech signals. Three cases are considered: normal speech, laughed-speech and nonspeech-laugh. A modified zero-frequency filtering method is proposed to extract source features. Parameters representing production features are derived to distinguish the 3 cases. These help studying discriminating characteristics of laughter from normal speech. Abstract: In this paper, the production characteristics of laughter are analysed at call and bout levels. Data of natural laughter is examined using electroglottograph (EGG) and acoustic signals. Nonspeech-laugh and laughed-speech are analysed in comparison with normal speech using features derived from the EGG and acoustic signals. Analysis of EGG signal is used to derive the average closed phase quotient in glottal cycles and the average instantaneous fundamental frequency ( F 0 ). Excitation source characteristics are analysed from the acoustic signal using a modified zero-frequency filtering (mZFF) method. Excitation impulse density and the strength of impulse-like excitation are extracted from the mZFF signal. Changes in the vocal tract system characteristics are examined in terms of the first two dominant frequencies derived using linear prediction (LP) analysis. Additional excitation information present in the acoustic signal is examined using a measure of sharpness of peaks in the Hilbert envelope of the LP residual at the glottal closure instants. Parameters representing degree of change and temporal changes in the production features are also derived to study the discriminating characteristics of laughter from normal speech. Changes are larger for nonspeech-laugh than laughed-speech, with reference to normal speech.