Abstract:The human voice carries socially relevant information such as how authoritative, dominant, and attractive the speaker sounds. However, some speakers may be able to manipulate listeners by modulating the shape and size of their vocal tract to exaggerate certain characteristics of their voice. We analysed the veridical size of speakers’ vocal tracts using real-time magnetic resonance imaging as they volitionally modulated their voice to sound larger or smaller, corresponding changes to the size implied by the ac… Show more
“…As for the average vocal tract outlines described above, plots of the fPC values for individual analysis frames show a relatively consistent pattern across participants, where volitional laughs lie intermediate between spontaneous laughs and vowels (see figures 3 c and 4 c ). An RShiny companion app to this article provides interactive visualization and data exploration from these fPCs individually or in combination (figure 5; [31]). Figure 5This article is accompanied by an interactive data visualization app with which the reader can explore the first four functional principal components of vocal tract shape during spontaneous laughter, volitional laughter and vowels.…”
Section: Resultsmentioning
confidence: 99%
“…As for the average vocal tract outlines described above, plots of the fPC values for individual analysis frames show a relatively consistent pattern across participants, where volitional laughs lie intermediate between spontaneous laughs and vowels (see figures 3c and 4c). An RShiny companion app to this article provides interactive visualization and data exploration from these fPCs individually or in combination (figure 5; [31]).…”
Section: (B) Functional Principal Components Analysismentioning
A substantial body of acoustic and behavioural evidence points to the existence of two broad categories of laughter in humans: spontaneous laughter that is emotionally genuine and somewhat involuntary, and volitional laughter that is produced on demand. In this study, we tested the hypothesis that these are also physiologically distinct vocalizations, by measuring and comparing them using real-time magnetic resonance imaging (rtMRI) of the vocal tract. Following Ruch and Ekman (Ruch and Ekman 2001 In
Emotions, qualia, and consciousness
(ed. A Kaszniak), pp. 426–443), we further predicted that spontaneous laughter should be relatively less speech-like (i.e. less articulate) than volitional laughter. We collected rtMRI data from five adult human participants during spontaneous laughter, volitional laughter and spoken vowels. We report distinguishable vocal tract shapes during the vocalic portions of these three vocalization types, where volitional laughs were intermediate between spontaneous laughs and vowels. Inspection of local features within the vocal tract across the different vocalization types offers some additional support for Ruch and Ekman's predictions. We discuss our findings in light of a dual pathway hypothesis for the neural control of human volitional and spontaneous vocal behaviours, identifying tongue shape and velum lowering as potential biomarkers of spontaneous laughter to be investigated in future research.
This article is part of the theme issue ‘Cracking the laugh code: laughter through the lens of biology, psychology and neuroscience’.
“…As for the average vocal tract outlines described above, plots of the fPC values for individual analysis frames show a relatively consistent pattern across participants, where volitional laughs lie intermediate between spontaneous laughs and vowels (see figures 3 c and 4 c ). An RShiny companion app to this article provides interactive visualization and data exploration from these fPCs individually or in combination (figure 5; [31]). Figure 5This article is accompanied by an interactive data visualization app with which the reader can explore the first four functional principal components of vocal tract shape during spontaneous laughter, volitional laughter and vowels.…”
Section: Resultsmentioning
confidence: 99%
“…As for the average vocal tract outlines described above, plots of the fPC values for individual analysis frames show a relatively consistent pattern across participants, where volitional laughs lie intermediate between spontaneous laughs and vowels (see figures 3c and 4c). An RShiny companion app to this article provides interactive visualization and data exploration from these fPCs individually or in combination (figure 5; [31]).…”
Section: (B) Functional Principal Components Analysismentioning
A substantial body of acoustic and behavioural evidence points to the existence of two broad categories of laughter in humans: spontaneous laughter that is emotionally genuine and somewhat involuntary, and volitional laughter that is produced on demand. In this study, we tested the hypothesis that these are also physiologically distinct vocalizations, by measuring and comparing them using real-time magnetic resonance imaging (rtMRI) of the vocal tract. Following Ruch and Ekman (Ruch and Ekman 2001 In
Emotions, qualia, and consciousness
(ed. A Kaszniak), pp. 426–443), we further predicted that spontaneous laughter should be relatively less speech-like (i.e. less articulate) than volitional laughter. We collected rtMRI data from five adult human participants during spontaneous laughter, volitional laughter and spoken vowels. We report distinguishable vocal tract shapes during the vocalic portions of these three vocalization types, where volitional laughs were intermediate between spontaneous laughs and vowels. Inspection of local features within the vocal tract across the different vocalization types offers some additional support for Ruch and Ekman's predictions. We discuss our findings in light of a dual pathway hypothesis for the neural control of human volitional and spontaneous vocal behaviours, identifying tongue shape and velum lowering as potential biomarkers of spontaneous laughter to be investigated in future research.
This article is part of the theme issue ‘Cracking the laugh code: laughter through the lens of biology, psychology and neuroscience’.
“…Previous work has shown gender differences in some acoustic parameters associated with expressing social traits in the voice (Hughes et al, 2014), as well as specific modulation performance (Belyk et al, 2022). Although these might be more important in mating contexts, which often rely on exaggerations of sexually dimorphic physical characteristics (Fraccaro et al, 2013;B.…”
Section: Considerations and Further Studiesmentioning
confidence: 99%
“…Using the voice effectively to achieve favourable trait judgments from listeners might be an important tool in social interactions. Nevertheless, speakers differ considerably in their ability to modulate their voice on demand (Belyk et al, 2022). So, what are the speaker characteristics that influence volitional voice modulation?…”
Section: Speaker Differences In Volitional Voice Modulation Reflected...mentioning
How we use our voice is central to how we express information about ourselves to others. A speaker’s dispositional social reactivity might contribute to how well they can volitionally modulate their voice to manage listener impressions. Here, we investigated individual differences in social vocal control performance in relation to social reactivity indices and underlying neural mechanisms. Twenty-four right-handed speakers of British English (twenty females) modulated their voice to communicate social traits (sounding likeable, hostile, intelligent) while undergoing a rapid-sparse fMRI protocol. Performance in social vocal control was operationalized as the specificity with which speakers evoked trait percepts in an independent group of naïve listeners. Speakers’ empathy levels, as well as psychopathic and Machiavellian traits, were assessed using self-report questionnaires. The ability to express specific social traits in voices was associated with activation in brain regions involved in vocal motor and social processing (left posterior TPJ, bilateral SMG, premotor cortex). While dispositional cognitive empathy predicted general vocal performance, self-reported levels of Machiavellianism were specifically related to better performance in expressing likeability. These findings highlight the psychological and neural mechanisms involved in strategic social voice modulation, suggesting differential processing in a combined network of vocal control and social processing streams.
“…FD reflects the vocal tract length -which is also closely tied to body size [24]. Speakers can extend (lower FD) or shorten (higher FD) their vocal tract [25] through facial expressions: previous results have reported an association between FD and expressions of emotions such as smiles [26] and disgust [27]. However, FD does not allow for an exhaustive description of the underlying articulatory strategies, e.g.…”
Humans have an impressive ability to communicate precise social intentions and desires with their voice -through vocal attitudes. Previous studies have shown how isolated acoustic features such as pitch can convey social attitudes, but have mostly worked with single attitudes and have not controlled for interspeaker variability. Thus, the vocal behaviours used to produce social attitudes remain mostly unknown. That is the aim of the current study, to uncover the anatomic production strategies that speakers use to communicate vocal attitudes. To do this, we analysed recordings from N=20 French speakers producing dominant, friendly, seductive and distant speech. For each of these attitudes, we investigated their vocal fold behaviour, vocal tract actuation and phonetic speech structure, with the support of deep alignment methods, and compared them with group statistics. We notably produced high-level representations of speakers' articulation (e.g. Vowel Space Density) and speech rhythm. Our results reveal speakers' prototypical strategies to produce vocal attitudes, and highlight how vocal behaviours can communicate social signals. We expect these results to provide an objective validation method for deep voice attitude conversions.
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