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When listeners hear a voice, they rapidly form a complex first impression of who the person behind that voice might be. We characterize how these multivariate first impressions from voices emerge over time across different levels of abstraction using electroencephalography and representational similarity analysis. We find that for eight perceived physical (gender, age, and health), trait (attractiveness, dominance, and trustworthiness), and social characteristics (educatedness and professionalism), representations emerge early (~80 ms after stimulus onset), with voice acoustics contributing to those representations between ~100 ms and 400 ms. While impressions of person characteristics are highly correlated, we can find evidence for highly abstracted, independent representations of individual person characteristics. These abstracted representationse merge gradually over time. That is, representations of physical characteristics (age, gender) arise early (from ~120 ms), while representations of some trait and social characteristics emerge later (~360 ms onward). The findings align with recent theoretical models and shed light on the computations underpinning person perception from voices., Competing Interests: Competing interests statement:The authors declare no competing interest.

Unimodal and cross-modal information provided by faces and voices contribute to identity percepts. To examine how these sources of information interact, we devised a novel audio-visual sorting task in which participants were required to group video-only and audio-only clips into two identities. In a series of three experiments, we show that unimodal face and voice sorting were more accurate than cross-modal sorting: While face sorting was consistently most accurate followed by voice sorting, cross-modal sorting was at chancel level or below. In Experiment 1, we compared performance in our novel audio-visual sorting task to a traditional identity matching task, showing that unimodal and cross-modal identity perception were overall moderately more accurate than the traditional identity matching task. In Experiment 2, separating unimodal from cross-modal sorting led to small improvements in accuracy for unimodal sorting, but no change in cross-modal sorting performance. In Experiment 3, we explored the effect of minimal audio-visual training: Participants were shown a clip of the two identities in conversation prior to completing the sorting task. This led to small, nonsignificant improvements in accuracy for unimodal and cross-modal sorting. Our results indicate that unfamiliar face and voice perception operate relatively independently with no evidence of mutual benefit, suggesting that extracting reliable cross-modal identity information is challenging., (© 2021. The Author(s).)

High variability training has been shown to benefit the learning of new face identities. In three experiments, we investigated whether this is also the case for voice identity learning. In Experiment 1a, we contrasted high variability training sets - which included stimuli extracted from a number of different recording sessions, speaking environments and speaking styles - with low variability stimulus sets that only included a single speaking style (read speech) extracted from one recording session (see Ritchie & Burton, 2017 for faces). Listeners were tested on an old/new recognition task using read sentences (i.e. test materials fully overlapped with the low variability training stimuli) and we found a high variability disadvantage. In Experiment 1b, listeners were trained in a similar way, however, now there was no overlap in speaking style or recording session between training sets and test stimuli. Here, we found a high variability advantage. In Experiment 2, variability was manipulated in terms of the number of unique items as opposed to number of unique speaking styles. Here, we contrasted the high variability training sets used in Experiment 1a with low variability training sets that included the same breadth of styles, but fewer unique items; instead, individual items were repeated (see Murphy, Ipser, Gaigg, & Cook, 2015 for faces). We found only weak evidence for a high variability advantage, which could be explained by stimulus-specific effects. We propose that high variability advantages may be particularly pronounced when listeners are required to generalise from trained stimuli to different-sounding, previously unheard stimuli. We discuss these findings in the context of mechanisms thought to underpin advantages for high variability training., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The human voice is a highly flexible instrument for self-expression, yet voice identity perception is largely studied using controlled speech recordings. Using two voice-sorting tasks with naturally varying stimuli, we compared the performance of listeners who were familiar and unfamiliar with the TV show Breaking Bad . Listeners organised audio clips of speech with (1) low-expressiveness and (2) high-expressiveness into perceived identities. We predicted that increased expressiveness (e.g., shouting, strained voice) would significantly impair performance. Overall, while unfamiliar listeners were less able to generalise identity across exemplars, the two groups performed equivalently well when telling voices apart when dealing with low-expressiveness stimuli. However, high vocal expressiveness significantly impaired telling apart in both the groups: this led to increased misidentifications , where sounds from one character were assigned to the other. These misidentifications were highly consistent for familiar listeners but less consistent for unfamiliar listeners. Our data suggest that vocal flexibility has powerful effects on identity perception, where changes in the acoustic properties of vocal signals introduced by expressiveness lead to effects apparent in familiar and unfamiliar listeners alike. At the same time, expressiveness appears to have affected other aspects of voice identity processing selectively in one listener group but not the other, thus revealing complex interactions of stimulus properties and listener characteristics (i.e., familiarity) in identity processing.

Our voices sound different depending on the context (laughing vs. talking to a child vs. giving a speech), making within-person variability an inherent feature of human voices. When perceiving speaker identities, listeners therefore need to not only 'tell people apart' (perceiving exemplars from two different speakers as separate identities) but also 'tell people together' (perceiving different exemplars from the same speaker as a single identity). In the current study, we investigated how such natural within-person variability affects voice identity perception. Using voices from a popular TV show, listeners, who were either familiar or unfamiliar with this show, sorted naturally varying voice clips from two speakers into clusters to represent perceived identities. Across three independent participant samples, unfamiliar listeners perceived more identities than familiar listeners and frequently mistook exemplars from the same speaker to be different identities. These findings point towards a selective failure in 'telling people together'. Our study highlights within-person variability as a key feature of voices that has striking effects on (unfamiliar) voice identity perception. Our findings not only open up a new line of enquiry in the field of voice perception but also call for a re-evaluation of theoretical models to account for natural variability during identity perception., (© 2018 The Authors. British Journal of Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Human voices are extremely variable: The same person can sound very different depending on whether they are speaking, laughing, shouting or whispering. In order to successfully recognise someone from their voice, a listener needs to be able to generalize across these different vocal signals ('telling people together'). However, in most studies of voice-identity processing to date, the substantial within-person variability has been eliminated through the use of highly controlled stimuli, thus focussing on how we tell people apart. We argue that this obscures our understanding of voice-identity processing by controlling away an essential feature of vocal stimuli that may include diagnostic information. In this paper, we propose that we need to extend the focus of voice-identity research to account for both "telling people together" as well as "telling people apart." That is, we must account for whether, and to what extent, listeners can overcome within-person variability to obtain a stable percept of person identity from vocal cues. To do this, our theoretical and methodological frameworks need to be adjusted to explicitly include the study of within-person variability.

We present an investigation of the perception of authenticity in audiovisual laughter, in which we contrast spontaneous and volitional samples and examine the contributions of unimodal affective information to multimodal percepts. In a pilot study, we demonstrate that listeners perceive spontaneous laughs as more authentic than volitional ones, both in unimodal (audio-only, visual-only) and multimodal contexts (audiovisual). In the main experiment, we show that the discriminability of volitional and spontaneous laughter is enhanced for multimodal laughter. Analyses of relationships between affective ratings and the perception of authenticity show that, while both unimodal percepts significantly predict evaluations of audiovisual laughter, it is auditory affective cues that have the greater influence on multimodal percepts. We discuss differences and potential mismatches in emotion signalling through voices and faces, in the context of spontaneous and volitional behaviour, and highlight issues that should be addressed in future studies of dynamic multimodal emotion processing.

Previous investigations of vocal expressions of emotion have identified acoustic and perceptual distinctions between expressions of different emotion categories, and between spontaneous and volitional (or acted) variants of a given category. Recent work on laughter has identified relationships between acoustic properties of laughs and their perceived affective properties (arousal and valence) that are similar across spontaneous and volitional types (Bryant & Aktipis, 2014; Lavan et al., 2016). In the current study, we explored the neural correlates of such relationships by measuring modulations of the BOLD response in the presence of itemwise variability in the subjective affective properties of spontaneous and volitional laughter. Across all laughs, and within spontaneous and volitional sets, we consistently observed linear increases in the response of bilateral auditory cortices (including Heschl's gyrus and superior temporal gyrus [STG]) associated with higher ratings of perceived arousal, valence and authenticity. Areas in the anterior medial prefrontal cortex (amPFC) showed negative linear correlations with valence and authenticity ratings across the full set of spontaneous and volitional laughs; in line with previous research (McGettigan et al., 2015; Szameitat et al., 2010), we suggest that this reflects increased engagement of these regions in response to laughter of greater social ambiguity. Strikingly, an investigation of higher-order relationships between the entire laughter set and the neural response revealed a positive quadratic profile of the BOLD response in right-dominant STG (extending onto the dorsal bank of the STS), where this region responded most strongly to laughs rated at the extremes of the authenticity scale. While previous studies claimed a role for right STG in bipolar representation of emotional valence, we instead argue that this may in fact exhibit a relatively categorical response to emotional signals, whether positive or negative., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Humans can generate mental auditory images of voices or songs, sometimes perceiving them almost as vividly as perceptual experiences. The functional networks supporting auditory imagery have been described, but less is known about the systems associated with interindividual differences in auditory imagery. Combining voxel-based morphometry and fMRI, we examined the structural basis of interindividual differences in how auditory images are subjectively perceived, and explored associations between auditory imagery, sensory-based processing, and visual imagery. Vividness of auditory imagery correlated with gray matter volume in the supplementary motor area (SMA), parietal cortex, medial superior frontal gyrus, and middle frontal gyrus. An analysis of functional responses to different types of human vocalizations revealed that the SMA and parietal sites that predict imagery are also modulated by sound type. Using representational similarity analysis, we found that higher representational specificity of heard sounds in SMA predicts vividness of imagery, indicating a mechanistic link between sensory- and imagery-based processing in sensorimotor cortex. Vividness of imagery in the visual domain also correlated with SMA structure, and with auditory imagery scores. Altogether, these findings provide evidence for a signature of imagery in brain structure, and highlight a common role of perceptual-motor interactions for processing heard and internally generated auditory information., (© The Author 2015. Published by Oxford University Press.)

It is well established that categorising the emotional content of facial expressions may differ depending on contextual information. Whether this malleability is observed in the auditory domain and in genuine emotion expressions is poorly explored. We examined the perception of authentic laughter and crying in the context of happy, neutral and sad facial expressions. Participants rated the vocalisations on separate unipolar scales of happiness and sadness and on arousal. Although they were instructed to focus exclusively on the vocalisations, consistent context effects were found: For both laughter and crying, emotion judgements were shifted towards the information expressed by the face. These modulations were independent of response latencies and were larger for more emotionally ambiguous vocalisations. No effects of context were found for arousal ratings. These findings suggest that the automatic encoding of contextual information during emotion perception generalises across modalities, to purely non-verbal vocalisations, and is not confined to acted expressions.