This study examined what determines typicality (gradedstructure) in vocal expressions of emotion. Separate groups ofjudges rated expressive speech stimuli (both acted andspontaneous expressions) with regard to typicality, ideality,and frequency of instantiation (FI). Also, a measure ofsimilarity to central tendency (CT) was obtained from listenerjudgments. Partial correlations and multiple regressionanalysis revealed that similarity to ideal, and not FI or CT,explained most variance in judged typicality. It is argued thatthese results may indicate that prototypical vocal expressionsare best characterized as goal-derived categories, rather thancommon taxonomic categories. This could explain howprototypical expressions can be acoustically distinct andhighly recognizable, while at the same time occur relativelyrarely in everyday speech.
Which emotions are associated with universally recognized non-verbal signals?We address this issue by examining how reliably non-linguistic vocalizations (affect bursts) can convey emotions across cultures. Actors from India, Kenya, Singapore, and USA were instructed to produce vocalizations that would convey nine positive and nine negative emotions to listeners. The vocalizations were judged by Swedish listeners using a within-valence forced-choice procedure, where positive and negative emotions were judged in separate experiments. Results showed that listeners could recognize a wide range of positive and negative emotions with accuracy above chance. For positive emotions, we observed the highest recognition rates for relief, followed by lust, interest, serenity and positive surprise, with affection and pride receiving the lowest recognition rates. Anger, disgust, fear, sadness, and negative surprise received the highest recognition rates for negative emotions, with the lowest rates observed for guilt and shame. By way of summary, results showed that the voice can reveal both basic emotions and several positive emotions other than happiness across cultures, but self-conscious emotions such as guilt, pride, and shame seem not to be well recognized from non-linguistic vocalizations.
Empirical studies have indicated that listeners value music primarily for its ability to arouse emotions. Yet little is known about which emotions listeners normally experience when listening to music, or about the causes of these emotions. The goal of this study was therefore to explore the prevalence of emotional reactions to music in everyday life and how this is influenced by various factors in the listener, the music, and the situation. A self-administered mail questionnaire was sent to a random and nationally representative sample of 1,500 Swedish citizens between the ages of 18 and 65, and 762 participants (51%) responded to the questionnaire. Thirty-two items explored both musical emotions in general (semantic estimates) and the most recent emotion episode featuring music for each participant (episodic estimates). The results revealed several variables (e.g., personality, age, gender, listener activity) that were correlated with particular emotions. A multiple discriminant analysis indicated that three of the most common emotion categories in a set of musical episodes (i.e., happiness, sadness, nostalgia) could be predicted with a mean accuracy of 70% correct based on data obtained from the questionnaire. The results may inform theorizing about musical emotions and guide the selection of causal variables for manipulation in future experiments.
Abstract Age-related differences in emotion recognition have predominantly been investigated using static pictures of facial expressions, and positive emotions beyond happiness have rarely been included. The current study instead used dynamic facial and vocal stimuli, and included a wider than usual range of positive emotions. In Task 1, younger and older adults were tested for their abilities to recognize 12 emotions from brief video recordings presented in visual, auditory, and multimodal blocks. Task 2 assessed recognition of 18 emotions conveyed by non-linguistic vocalizations (e.g., laughter, sobs, and sighs). Results from both tasks showed that younger adults had significantly higher overall recognition rates than older adults. In Task 1, significant group differences (younger > older) were only observed for the auditory block (across all emotions), and for expressions of anger, irritation, and relief (across all presentation blocks). In Task 2, significant group differences were observed for 6 out of 9 positive, and 8 out of 9 negative emotions. Overall, results indicate that recognition of both positive and negative emotions show age-related differences. This suggests that the age-related positivity effect in emotion recognition may become less evident when dynamic emotional stimuli are used and happiness is not the only positive emotion under study.
Introduction: Schizophrenia patients show decreased ability to identify emotion based upon tone of voice (voice emotion recognition), along with deficits in basic auditory processing. Interrelationship among these measures is poorly understood. Methods: Forty-one patients with schizophrenia/schizoaffective disorder and 41 controls were asked to identify the emotional valence (happy, sad, angry, fear, or neutral) of 38 synthesized frequency-modulated (FM) tones designed to mimic key acoustic features of human vocal expressions. The mean (F0M) and variability (F0SD) of fundamental frequency (pitch) and absence or presence of high frequency energy (HF500) of the tones were independently manipulated to assess contributions on emotion identification. Forty patients and 39 controls also completed tone-matching and voice emotion recognition tasks. Results: Both groups showed a nonrandom response pattern (P < .0001). Stimuli with highest and lowest F0M/F0SD were preferentially identified as happy and sad, respectively. Stimuli with low F0M and midrange F0SD values were identified as angry. Addition of HF500 increased rates of angry and decreased rates of sad identifications. Patients showed less differentiation of response across frequency changes, leading to a highly significant between-group difference in response pattern to maximally identifiable stimuli (d = 1.4). The differential identification pattern for FM tones correlated with deficits in basic tone-matching ability (P = .01), voice emotion recognition (P < .001), and negative symptoms (P < .001). Conclusions: Specific FM tones conveyed reliable emotional percepts in both patients and controls and correlated highly with deficits in ability to recognize information based upon tone of voice, suggesting significant bottom-up contributions to social cognition and negative symptom impairments in schizophrenia.
Affective dysprosodia, or deficits in the perception of emotion through vocal intonation, are an enduring aspect of schizophrenia that are linked to negative symptoms and predicted by sensory processing dysfunction. Yet the taxonomy or affective specificity in patient dysprosodia is unknown. Within prosody in particular, it has been difficult to disentangle emotion specific deficits from differences in emotion intensity perception. Prior research has shown that certain acoustical cues such as fundamental frequency (F0), voice intensity (VOint) and high frequency energy (HF-500) are highly predictive of decoding ability. Here, we examined patients’ perception of 5 basic emotions at differing intensity levels in conjunction with intensity ratings. Additionally, we examined the relationship between performance and intensity ratings and acoustical properties of the stimuli in an emotion specific manner. In a sample of 26 patients with schizophrenia/schizoaffective disorder and 17 healthy controls we found the following: Patient decoding was significantly worse for all affective classifications save angry, and there was no significant emotion x group interaction or intensity x group nteraction. Correlation analysis between affective decoding and the acoustic properties of the stimuli revealed that patients were significantly less sensitive to changes in F0sd, and that these differences contributed to differential decoding ability of happy, sad and fearful utterances. Analysis of affective decoding misattribution patterns revealed that patients and controls had generally the same types of misattribution errors, and further, that deviations from the control misattribution pattern were in part related to acoustic cue utilization. Finally, patient ratings of emotional intensity were slightly higher than those of controls. These results suggest that patients’ affective dysprosodia is not characterized by any experiential deficit or differences along arousal or valence dimensions but rather, stem from aberrant sensorial and cognitive processing.
We present intra-, inter- and cross-cultural classifications of vocal expressions. Stimuli were selected from the VENEC corpus and consisted of portrayals of 11 emotions, each expressed with 3 leve ...
It has been the matter of much debate whether perceivers are able to distinguish spontaneous vocal expressions of emotion from posed vocal expressions (e.g., emotion portrayals). In this experiment, we show that such discrimination can be manifested in the autonomic arousal of listeners during implicit processing of vocal emotions. Participants (N = 21, age: 20-55 years) listened to two consecutive blocks of brief voice clips and judged the gender of the speaker in each clip, while we recorded three measures of sympathetic arousal of the autonomic nervous system (skin conductance level, mean arterial blood pressure, pulse rate). Unbeknownst to the listeners, the blocks consisted of two types of emotional speech: spontaneous and posed clips. As predicted, spontaneous clips yielded higher arousal levels than posed clips, suggesting that listeners implicitly distinguished between the two kinds of expression, even in the absence of any requirement to retrieve emotional information from the voice. We discuss the results with regard to theories of emotional contagion and the use of posed stimuli in studies of emotions.
