Abstract
Laughter is one of the most common non-verbal features; however, contrary to the previous assumptions, it may also act as signals of bonding, affection, emotional regulation agreement or empathy (Scott et al. Trends Cogn Sci 18:618-620, 2014). Although previous research agrees that laughter does not form a uniform group in many respects, different types of laughter have been defined differently by individual research. Due to the various definitions of laughter, as well as their different methodologies, the results of the previous examinations were often contradictory. The analysed laughs were often recorded in controlled, artificial situations; however, less is known about laughs from social conversations. Thus, the aim of the present study is to examine the acoustic realisation, as well as the automatic classification of laughter that appear in human interactions according to whether listeners consider them to be voluntary or involuntary. The study consists of three parts using a multi-method approach. Firstly, in the perception task, participants had to decide whether the given laughter seemed to be rather involuntary or voluntary. In the second part of the experiment, those sound samples of laughter were analysed that were considered to be voluntary or involuntary by at least 66.6% of listeners. In the third part, all the sound samples were grouped into the two categories by an automatic classifier. The results showed that listeners were able to distinguish laughter extracted from spontaneous conversation into two different types, as well as the distinction was possible on the basis of the automatic classification. In addition, there were significant differences in acoustic parameters between the two groups of laughter. The results of the research showed that, although the distinction between voluntary and involuntary laughter categories appears based on the analysis of everyday, spontaneous conversations in terms of the perception and acoustic features, there is often an overlap in the acoustic features of voluntary and involuntary laughter. The results will enrich our previous knowledge of laughter and help to describe and explore the diversity of non-verbal vocalisations.