Voice Production and Perception

The voice is a prime channel of communication in humans and other animals. Voices convey many kinds of information, including physical characteristics like body size and sex, as well as providing cues to the vocalizing individual’s identity and emotional state. Vocalizations are produced by dynamic modifications of the physiological vocal production system. The source-filter theory explains how vocalizations are produced in two stages: (a) the production of a sound source in the larynx, and (b) the filtering of that sound by the vocal tract. This two-stage process largely applies to all primate vocalizations. However, there are some differences between the vocal production apparatus of humans as compared to nonhuman primates, such as the lower position of the larynx and lack of air sacs in humans. Thanks to our flexible vocal apparatus, humans can produce a range of different types of vocalizations, including spoken language, nonverbal vocalizations, whispering, and singing. A comprehensive understanding of vocal communication takes both production and perception of vocalizations into account. Internal processes are expressed in the form of specific acoustic patterns in the producer’s voice. In order to communicate information in vocalizations, those acoustic patterns must be acoustically registered by listeners via auditory perception mechanisms. Both production and perception of vocalizations are affected by psychobiological mechanisms as well as sociocultural factors. Furthermore, vocal production and perception can be impaired by a range of different disorders. Vocal production and hearing disorders, as well as mental disorders including autism spectrum disorder, depression, and schizophrenia, affect vocal communication

Good vibrations: A review of vocal expressions of positive emotions

Researchers examining nonverbal communication of emotions are becoming increasingly interested in differentiations between different positive emotional states like interest, relief, and pride. But despite the importance of the voice in communicating emotion in general and positive emotion in particular, there is to date no systematic review of what characterizes vocal expressions of different positive emotions. Furthermore, integration and synthesis of current findings are lacking. In this review, we comprehensively review studies (N = 108) investigating acoustic features relating to specific positive emotions in speech prosody and nonverbal vocalizations. We find that happy voices are generally loud with considerable variability in loudness, have high and variable pitch, and are high in the first two formant frequencies. When specific positive emotions are directly compared with each other, pitch mean, loudness mean, and speech rate differ across positive emotions, with patterns mapping onto clusters of emotions, so-called emotion families. For instance, pitch is higher for epistemological emotions (amusement, interest, relief), moderate for savouring emotions (contentment and pleasure), and lower for a prosocial emotion (admiration). Some, but not all, of the differences in acoustic patterns also map on to differences in arousal levels. We end by pointing to limitations in extant work and making concrete proposals for future research on positive emotions in the voice

Perception of group membership from spontaneous and volitional laughter

Laughter is a ubiquitous social signal. Recent work has highlighted distinctions between spontaneous and volitional laughter, which differ in terms of both production mechanisms and perceptual features. Here, we test listeners’ ability to infer group identity from volitional and spontaneous laughter, as well as the perceived positivity of these laughs across cultures. Dutch (n = 273) and Japanese (n = 131) participants listened to decontextualized laughter clips and judged 1) whether the laughing person was from their cultural in-group or an out-group; and 2) whether they thought the laughter was produced spontaneously or volitionally. They also rated the positivity of each laughter clip. Using frequentist and Bayesian analyses, we show that listeners were able to infer group membership from both spontaneous and volitional laughter, and that performance was equivalent for both types of laughter. Spontaneous laughter was rated as more positive than volitional laughter across the two cultures, and in-group laughs were perceived as more positive than out-group laughs by Dutch but not Japanese listeners. Our results demonstrate that both spontaneous and volitional laughter can be used by listeners to infer laughers’ cultural group identity