Covert digital manipulation of vocal emotion alter speakers' emotional states in a congruent direction

Prosody-focused feedback enhances the efficacy of anti-depressive self-statements in depressed individuals - A randomized controlled trial

This study was aimed to evaluate whether the efficacy of invoking anti-depressive self-statements to cope with depressed mood can be enhanced for depressed individuals by systematically guiding them to amplify the expression of conviction in their voice. Accordingly, we recruited N = 144 participants (48 clinically depressed individuals, 48 sub-clinically depressed individuals, and 48 non-depressed individuals). Participants were randomly assigned to an experimental or control condition. Across study conditions, participants completed a mood induction procedure, then read aloud scripted anti-depressive self-statements designed to reduce depressed mood. Participants in the experimental condition received instructions to heighten the prosodic expression of conviction in their voice; participants in the control condition received no prosodic expression instructions. Results showed that depressed participants achieved a more pronounced decrease of depressed mood in the experimental condition than in the control condition. Further, the results indicated no effects in sub-clinically depressed and non-depressed individuals. Finally, heightened conviction expressed by participants in the experimental condition was associated with lower depressed mood and diminished depressive symptom severity. Overall, our findings suggest that fostering the prosodic expression of conviction in depressed persons' voices, while they vocalize anti-depressive self-statements, represents a promising method for augmenting the efficacy of cognitive interventions for depression.

Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments

People have a well-described advantage in identifying individuals and emotions in their own culture, a phenomenon also known as the other-race and language-familiarity effect. However, it is unclear whether native-language advantages arise from genuinely enhanced capacities to extract relevant cues in familiar speech or, more simply, from cultural differences in emotional expressions. Here, to rule out production differences, we use algorithmic voice transformations to create French and Japanese stimulus pairs that differed by exactly the same acoustical characteristics. In two cross-cultural experiments, participants performed better in their native language when categorizing vocal emotional cues and detecting non-emotional pitch changes. This advantage persisted over three types of stimulus degradation (jabberwocky, shuffled and reversed sentences), which disturbed semantics, syntax, and supra-segmental patterns, respectively. These results provide evidence that production differences are not the sole drivers of the language-familiarity effect in cross-cultural emotion perception. Listeners' unfamiliarity with the phonology of another language, rather than with its syntax or semantics, impairs the detection of pitch prosodic cues and, in turn, the recognition of expressive prosody.

A voice without a mouth no more: The neurobiology of language and consciousness

Most research on the neurobiology of language ignores consciousness and vice versa. Here, language, with an emphasis on inner speech, is hypothesised to generate and sustain self-awareness, i.e., higher-order consciousness. Converging evidence supporting this hypothesis is reviewed. To account for these findings, a 'HOLISTIC' model of neurobiology of language, inner speech, and consciousness is proposed. It involves a 'core' set of inner speech production regions that initiate the experience of feeling and hearing words. These take on affective qualities, deriving from activation of associated sensory, motor, and emotional representations, involving a largely unconscious dynamic 'periphery', distributed throughout the whole brain. Responding to those words forms the basis for sustained network activity, involving 'default mode' activation and prefrontal and thalamic/brainstem selection of contextually relevant responses. Evidence for the model is reviewed, supporting neuroimaging meta-analyses conducted, and comparisons with other theories of consciousness made. The HOLISTIC model constitutes a more parsimonious and complete account of the 'neural correlates of consciousness' that has implications for a mechanistic account of mental health and wellbeing.

The shallow of your smile: the ethics of expressive vocal deep-fakes

Rapid technological advances in artificial intelligence are creating opportunities for real-time algorithmic modulations of a person's facial and vocal expressions, or 'deep-fakes'. These developments raise unprecedented societal and ethical questions which, despite much recent public awareness, are still poorly understood from the point of view of moral psychology. We report here on an experimental ethics study conducted on a sample of N = 303 participants (predominantly young, western and educated), who evaluated the acceptability of vignettes describing potential applications of expressive voice transformation technology. We found that vocal deep-fakes were generally well accepted in the population, notably in a therapeutic context and for emotions judged otherwise difficult to control, and surprisingly, even if the user lies to their interlocutors about using them. Unlike other emerging technologies like autonomous vehicles, there was no evidence of social dilemma in which one would, for example, accept for others what they resent for themselves. The only real obstacle to the massive deployment of vocal deep-fakes appears to be situations where they are applied to a speaker without their knowing, but even the acceptability of such situations was modulated by individual differences in moral values and attitude towards science fiction. This article is part of the theme issue 'Voice modulation: from origin and mechanism to social impact (Part II)'.

Even violins can cry: specifically vocal emotional behaviours also drive the perception of emotions in non-vocal music

A wealth of theoretical and empirical arguments have suggested that music triggers emotional responses by resembling the inflections of expressive vocalizations, but have done so using low-level acoustic parameters (pitch, loudness, speed) that, in fact, may not be processed by the listener in reference to human voice. Here, we take the opportunity of the recent availability of computational models that allow the simulation of three specifically vocal emotional behaviours: smiling, vocal tremor and vocal roughness. When applied to musical material, we find that these three acoustic manipulations trigger emotional perceptions that are remarkably similar to those observed on speech and scream sounds, and identical across musician and non-musician listeners. Strikingly, this not only applied to singing voice with and without musical background, but also to purely instrumental material.

This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’.

Vocal signals only impact speakers' own emotions when they are self-attributed

Emotions are often accompanied by vocalizations whose acoustic features provide information about the physiological state of the speaker. Here, we ask if perceiving these affective signals in one's own voice has an impact on one's own emotional state, and if it is necessary to identify these signals as self-originated for the emotional effect to occur. Participants had to deliberate out loud about how they would feel in various familiar emotional scenarios, while we covertly manipulated their voices in order to make them sound happy or sad. Perceiving the artificial affective signals in their own voice altered participants' judgements about how they would feel in these situations. Crucially, this effect disappeared when participants detected the vocal manipulation, either explicitly or implicitly. The original valence of the scenarios also modulated the vocal feedback effect. These results highlight the role of the exteroception of self-attributed affective signals in the emergence of emotional feelings.

Beyond Correlation: Acoustic Transformation Methods for the Experimental Study of Emotional Voice and Speech

While acoustic analysis methods have become a commodity in voice emotion research, experiments that attempt not only to describe but to computationally manipulate expressive cues in emotional voice and speech have remained relatively rare. We give here a nontechnical overview of voice-transformation techniques from the audio signal-processing community that we believe are ripe for adoption in this context. We provide sound examples of what they can achieve, examples of experimental questions for which they can be used, and links to open-source implementations. We point at a number of methodological properties of these algorithms, such as being specific, parametric, exhaustive, and real-time, and describe the new possibilities that these open for the experimental study of the emotional voice.

Happy you, happy me: expressive changes on a stranger's voice recruit faster implicit processes than self-produced expressions

In social interactions, people have to pay attention both to the ‘what’ and ‘who’. In particular, expressive changes heard on speech signals have to be integrated with speaker identity, differentiating e.g. self- and other-produced signals. While previous research has shown that self-related visual information processing is facilitated compared to non-self stimuli, evidence in the auditory modality remains mixed. Here, we compared electroencephalography (EEG) responses to expressive changes in sequence of self- or other-produced speech sounds using a mismatch negativity (MMN) passive oddball paradigm. Critically, to control for speaker differences, we used programmable acoustic transformations to create voice deviants that differed from standards in exactly the same manner, making EEG responses to such deviations comparable between sequences. Our results indicate that expressive changes on a stranger’s voice are highly prioritized in auditory processing compared to identical changes on the self-voice. Other-voice deviants generate earlier MMN onset responses and involve stronger cortical activations in a left motor and somatosensory network suggestive of an increased recruitment of resources for less internally predictable, and therefore perhaps more socially relevant, signals.

Soundgen: An open-source tool for synthesizing nonverbal vocalizations

Voice synthesis is a useful method for investigating the communicative role of different acoustic features. Although many text-to-speech systems are available, researchers of human nonverbal vocalizations and bioacousticians may profit from a dedicated simple tool for synthesizing and manipulating natural-sounding vocalizations. Soundgen ( https://CRAN.R-project.org/package=soundgen ) is an open-source R package that synthesizes nonverbal vocalizations based on meaningful acoustic parameters, which can be specified from the command line or in an interactive app. This tool was validated by comparing the perceived emotion, valence, arousal, and authenticity of 60 recorded human nonverbal vocalizations (screams, moans, laughs, and so on) and their approximate synthetic reproductions. Each synthetic sound was created by manually specifying only a small number of high-level control parameters, such as syllable length and a few anchors for the intonation contour. Nevertheless, the valence and arousal ratings of synthetic sounds were similar to those of the original recordings, and the authenticity ratings were comparable, maintaining parity with the originals for less complex vocalizations. Manipulating the precise acoustic characteristics of synthetic sounds may shed light on the salient predictors of emotion in the human voice. More generally, soundgen may prove useful for any studies that require precise control over the acoustic features of nonspeech sounds, including research on animal vocalizations and auditory perception.

Social Cognition through the Lens of Cognitive and Clinical Neuroscience

Social cognition refers to a set of processes, ranging from perception to decision-making, underlying the ability to decode others' intentions and behaviors to plan actions fitting with social and moral, besides individual and economic considerations. Its centrality in everyday life reflects the neural complexity of social processing and the ubiquity of social cognitive deficits in different pathological conditions. Social cognitive processes can be clustered in three domains associated with (a) perceptual processing of social information such as faces and emotional expressions (social perception), (b) grasping others' cognitive or affective states (social understanding), and (c) planning behaviors taking into consideration others', in addition to one's own, goals (social decision-making). We review these domains from the lens of cognitive neuroscience, i.e., in terms of the brain areas mediating the role of such processes in the ability to make sense of others' behavior and plan socially appropriate actions. The increasing evidence on the “social brain” obtained from healthy young individuals nowadays constitutes the baseline for detecting changes in social cognitive skills associated with physiological aging or pathological conditions. In the latter case, impairments in one or more of the abovementioned domains represent a prominent concern, or even a core facet, of neurological (e.g., acquired brain injury or neurodegenerative diseases), psychiatric (e.g., schizophrenia), and developmental (e.g., autism) disorders. To pave the way for the other papers of this issue, addressing the social cognitive deficits associated with severe acquired brain injury, we will briefly discuss the available evidence on the status of social cognition in normal aging and its breakdown in neurodegenerative disorders. Although the assessment and treatment of such impairments is a relatively novel sector in neurorehabilitation, the evidence summarized here strongly suggests that the development of remediation procedures for social cognitive skills will represent a future field of translational research in clinical neuroscience.

DAVID: An open-source platform for real-time transformation of infra-segmental emotional cues in running speech

We present an open-source software platform that transforms emotional cues expressed by speech signals using audio effects like pitch shifting, inflection, vibrato, and filtering. The emotional transformations can be applied to any audio file, but can also run in real time, using live input from a microphone, with less than 20-ms latency. We anticipate that this tool will be useful for the study of emotions in psychology and neuroscience, because it enables a high level of control over the acoustical and emotional content of experimental stimuli in a variety of laboratory situations, including real-time social situations. We present here results of a series of validation experiments aiming to position the tool against several methodological requirements: that transformed emotions be recognized at above-chance levels, valid in several languages (French, English, Swedish, and Japanese) and with a naturalness comparable to natural speech.

Auditory traits of "own voice"

People perceive their recorded voice differently from their actively spoken voice. The uncanny valley theory proposes that as an object approaches humanlike characteristics, there is an increase in the sense of familiarity; however, eventually a point is reached where the object becomes strangely similar and makes us feel uneasy. The feeling of discomfort experienced when people hear their recorded voice may correspond to the floor of the proposed uncanny valley. To overcome the feeling of eeriness of own-voice recordings, previous studies have suggested equalization of the recorded voice with various types of filters, such as step, bandpass, and low-pass, yet the effectiveness of these filters has not been evaluated. To address this, the aim of experiment 1 was to identify what type of voice recording was the most representative of one’s own voice. The voice recordings were presented in five different conditions: unadjusted recorded voice, step filtered voice, bandpass filtered voice, low-pass filtered voice, and a voice for which the participants freely adjusted the parameters. We found large individual differences in the most representative own-voice filter. In order to consider roles of sense of agency, experiment 2 investigated if lip-synching would influence the rating of own voice. The result suggested lip-synching did not affect own voice ratings. In experiment 3, based on the assumption that the voices used in previous experiments corresponded to continuous representations of non-own voice to own voice, the existence of an uncanny valley was examined. Familiarity, eeriness, and the sense of own voice were rated. The result did not support the existence of an uncanny valley. Taken together, the experiments led us to the following conclusions: there is no general filter that can represent own voice for everyone, sense of agency has no effect on own voice rating, and the uncanny valley does not exist for own voice, specifically.

Affective Prosody and Depression After Stroke: A Pilot Study

BACKGROUND AND PURPOSE

Poststroke depression (PSD) is a frequent complication of stroke with detrimental consequences in terms of quality of life and functional outcomes. In individuals with major depression, several studies have demonstrated an alteration of affective prosody. The aim of this study is to identify prosodic markers that may be predictive of PSD.

METHODS

Patient voices were recorded at baseline and 3 months after stroke. We extracted prosodic parameters, including fundamental frequency, percentage of voice breaks, and shimmer. Depression and anxiety symptoms were assessed 3 months later.

RESULTS

Among the 49 patients included in the study, 22.5% developed PSD 3 months after stroke. A significant decrease was observed concerning the fundamental frequency among patients who developed PSD. Discriminant analysis demonstrated that initial voice breaks coupled with shimmer are strongly predictive of subsequent PSD.

CONCLUSIONS

Early alterations of affective prosody are associated with a higher risk of PSD 3 months after a stroke. This new physiological approach overcomes traditional barriers associated with clinical instruments and contributes to the prediction of this disorder.

Emergency medical triage decisions are swayed by computer-manipulated cues of physical dominance in caller's voice

In humans as well as other animals, displays of body strength such as power postures or deep masculine voices are associated with prevalence in conflicts of interest and facilitated access to resources. We conduct here an ecological and highly critical test of this hypothesis in a domain that, on first thought, would appear to be shielded from such influences: access to emergency medical care. Using acoustic manipulations of vocal masculinity, we systematically varied the perceived level of physical dominance of mock patients calling a medical call center simulator. Callers whose voice were perceived as indicative of physical dominance (i.e. those with low fundamental and formant frequency voices) obtained a higher grade of response, a higher evaluation of medical emergency and longer attention from physicians than callers with strictly identical medical needs whose voice signaled lower physical dominance. Strikingly, while the effect was important for physician participants, it was virtually non-existent when calls were processed by non-medically-trained phone operators. This finding demonstrates an unprecedented degree of vulnerability of telephone-based medical decisions to extra-medical factors carried by vocal cues, and shows that it may not simply be assumed that more medical training will shield decisions from such influences.