This level of agreement is at the very least similar to the accuracy estimates seen in reviews of studies based primarily on posed expressions Scherer , most of which involve high intensity.
Stay in Touch
This supports the hypothesis that lower levels of agreement in studies which used spontaneous expressions are primarily due to lower levels of emotion intensity in the clips used. This can be related to findings showing that high-intensity portrayals produce higher levels of decoding accuracy than do low-intensity portrayals Juslin and Laukka It would appear that both spontaneous and posed vocal expressions involve more discrete and easily recognizable emotions as the intensity increases.
Similar results have been found in studies of facial expression Tassinary and Cacioppo The above conclusions notwithstanding, there are a number of limitations in the present experiments that should be acknowledged. First, we only included voice clips that consisted of a single grammatical sentence.
Strictly speaking, then, our conclusions must be limited to these conditions. Similarly, our database was limited to five European languages, for which we could obtain a sufficient collection of datasets. Because language could influence results in this domain Scherer , we should be wary of generalizing to other languages. One further limitation, mentioned in the pilot study, is that we were not able to obtain all datasets that met our criteria for inclusion, which is illustrative of more general problems in the present field, such as copyright or privacy restrictions, which prevent sharing of audio recordings.
It must be considered something of a failure that, after all recent efforts to create new emotion-in-speech databases, we experienced such difficulties in obtaining sufficiently large samples to systematically compare stimuli. Yet, we featured what is arguably the most representative sample of voice clips in any comparison of posed and spontaneous expressions so far, which strengthens our conclusions.
We also tried in all sorts of ways to make the comparisons as fair as possible, controlling for intensity, valence, verbal cues, and sound quality, and sampling voice clips in a randomized manner, to avoid selection bias. We would have preferred to control for individual emotions also, but this was not feasible, given the large disparity between the databases with regard to emotional content and annotations.
What are the implications of the present study for the use of posed vocal expressions in emotion research in general, and speech databases in particular?storminspasteson.tk/map16.php
Dance- An Expression Of Soul | Wrytin
One clear implication is that researchers need to be cautious—it cannot simply be assumed that posed clips will be similar to spontaneous ones. Having said that, the differences do not appear to be many and there are high-quality portrayals that may be indistinguishable from spontaneous expressions for most lay listeners. This shows that portrayals could fulfill the requirements of emotion researchers as long as they go through a quality check e.
To be fair, many researchers using emotion portrayals seem well aware of the risks and discuss various means to ensure that the portrayals are adequate Banse and Scherer ; Scherer et al. Notably, the use of professional actors does not seem to guarantee adequacy. It seems that a key task for the future is to develop better means to verify the quality of emotion portrayals.
12222 TOUR DATES & LOCATIONS
Doing so requires that we have an adequate understanding of spontaneous expressions. The present investigation shows that we still have some way to go in that respect. However, the present results in Study 1 and 2 strongly suggest that the distinction is meaningful: posed expressions were generally rated as less genuinely emotional and also tended to have different acoustic patterns. This much was apparent in the present studies, which exposed a number of flaws in current datasets with spontaneous and supposedly emotional speech. For example, the obtained overall differences in emotion intensity between spontaneous and posed datasets reflect in no small part that some spontaneous clips lacked emotion altogether.
The noted difficulty in obtaining spontaneous expressions of strong emotions Douglas-Cowie et al. The problem with such an approach is highlighted by the present investigation. A focus merely on low-intensity clips may lead to conclusions which are incomplete or misleading. Instead, they appear to differ with regard to more subtle acoustic nuances, which listeners may be able to detect. The precise nature of the voice cues that reveal genuine emotion remains to be described in future studies that take vocal expressions of all intensities into consideration.
Notably, the R software does not provide measures of effect size for the main effects and interactions of its robust ANOVA-type analyses, and due to a difference in computation, regular effect indices cannot be used. W denotes the Brunner Munzel test statistic with associated degrees of freedom, and p-hat is an estimate of the effect size in terms of the probability that a randomly taken score from one group will be greater or smaller than a randomly taken score from the other group i.
We acknowledge that this listener sample is smaller than in Study 1, which might influence the stability of our estimates. However, because we do not apply significance testing to the data, the risk of a Type II error is not an issue here. The present research was supported by a grant from the Bank of Sweden Tercentenary Foundation P Skip to main content Skip to sections.
Advertisement Hide. Download PDF. The Mirror to Our Soul? Open Access. First Online: 25 October Introduction It is commonly believed by lay people that nonverbal cues in the voice reveal our inner emotions to a listener. Spontaneous Versus Posed Expression At the heart of the criticism of using portrayals to study vocal expression of emotion is the distinction between spontaneous and posed vocal expression e.
Preliminary Comparisons It needs emphasizing that a comparison of spontaneous and posed expression should be divided into at least two questions: 1 Are the two types of expression perceptually different such that listeners can generally discriminate reliably between the two? Explaining Differences: The Role of Emotion Intensity One factor that could potentially account for reported differences between spontaneous and posed expression in the above studies is that the design did not control for differences in emotion intensity. Plutchik has suggested a structural model of emotions, which has the shape of a cone turned upside down Fig.
The circular structure describes the degree of similarity between emotions, whereas the vertical dimension represents their intensity. Thus, the top of the cone is a neutral center, from which an emotion moves towards a gradually more intense emotion at the bottom. This could help to explain earlier findings. Specifically, the difficulty in obtaining emotion-specific patterns of voice cues in spontaneous expressions might simply be due to the fact that the samples have featured a low emotion intensity, as compared to most emotion portrayals investigated so far Juslin Open image in new window.
Introduction The aim of the pilot study was to collect and evaluate a large and representative sample of audio clips featuring spontaneous and posed expressions with both low and high emotion intensity. Method Inclusion Criteria The primary criterion was to include only voice clips consisting of a single grammatical sentence. Search Strategy To identify potentially available voice recordings, we conducted a literature search of peer-reviewed journal articles published between and , scanned proceedings from conferences and workshops on emotional corpora e.
For each clip, he or she was required to rate emotion intensity, valence, verbal cues to emotion, and recording quality in accordance with the following instructions: Emotionality This refers to the extent to which the person talking sounds emotional or not. Valence This refers to whether it sounds like the person is having a positive pleasant feeling or a negative unpleasant feeling. Verbal Cues This refers to the extent to which the verbal content the actual words of the utterance helps you to infer something about the emotion felt by the speaker.
Sound Quality This refers to the perceived acoustic quality of the sound recording as such. Introduction The pilot study indicated that the main difference between the available voice clips of spontaneous and posed expressions concerned emotion intensity. Method Stimulus Material We used ratings from the pilot study to prepare a smaller set of spontaneous and posed voice clips that were matched concerning emotion intensity. The distribution of selected voice clips across original datasets is shown in Appendix 2.
Note that the spontaneous and posed samples have fairly similar means overall. The confidence intervals indicate that for medium and high intensity clips, the spontaneous clips featured more verbal cues than the posed clips, but the mean values for the spontaneous clips 1. Note also that high intensity clips had more negative valence—but this was true for both spontaneous and posed clips. The grand means bottom row for verbal cues and sound quality are relatively similar to those for the database as a whole Pilot Study , whereas the intensity is higher and the valence is lower than in the complete database.
These latter data directly reflect the sampling of three intensity levels, because higher intensities involve more negative valence see above and the database as a whole contains predominately low-intensity clips. They received the following instructions: You will soon hear a number of voice recordings containing women and men speaking in different languages. Although spontaneous clips were consistently rated as more genuinely emotional than posed clips, the difference was smaller for high-intensity than for medium- and low-intensity clips.
Introduction Study 1 showed that spontaneous vocal expressions were perceived as more genuinely emotional than posed expressions, even after controlling for differences in emotion intensity, and that the difference was not due to confounding factors such as emotional valence, verbal cues to emotion, or a difference in sound quality.
Method Acoustic Analysis All clips from the database were acoustically analyzed for the purposes of the present study. A principal components analysis varimax normalized rotation and casewise deletion of missing values was thus performed to reduce the number of cues included in subsequent statistical analysis. Outliers values 3 SD above or below the mean were excluded before data analysis in order to control for the occurrence of errors in the automatic extraction of cues e.
The number of factors to retain was assessed using parallel analysis, as implemented in the paran package in R Dinno , and revealed a factor solution. Based on the PCA results, we chose the cues with the highest loadings or interpretability for each factor. However, for two of the factors, there were no cues with loadings above.
In addition to the 11 cues chosen based on the PCA results, we also featured two cues proposed based on prior research: speech rate e. As may be seen, significant main effects of emotion were found for eight and five out of 13 cues for low and medium intensity clips, respectively, showing that several cues varied as a function of emotion. We conducted post hoc comparisons, in the form of robust rank-based, Tukey-type nonparametric contrasts, using the nparcomp R-package Konietschke et al.
Results indicated, for instance, that happy voice clips featured higher pitch level F0M than sad clips, and that angry clips featured a higher speech rate VoicedSegPerSec than sad clips. As already discussed, however, differences in overall levels might occur even within the same stimulus type e. Therefore they do not constitute strong evidence of a difference between spontaneous and posed expressions.
The effect of main interest for the question whether emotions are expressed differently in spontaneous expressions as compared to posed expressions is the stimulus type x emotion interaction. All significant interactions are displayed in Fig. Introduction Studies 1 and 2 indicated that spontaneous and posed expressions differ to some extent, both perceptually and acoustically. Results and Discussion Emotion recognition studies typically calculate measures of decoding accuracy, such as percentage of correct responses, but in our case it is not possible to calculate a direct measure of accuracy because for many of the included clips, we do not know which emotions they are supposed to express.
Note further that happiness was most common amongst the medium-intensity clips. Responses are most widely distributed across the emotion categories for the low-intensity clips. This can be interpreted as showing that these clips conveyed a large number of different emotions, but the low inter-rater agreement shown above suggests that a more parsimonious explanation is that low-intensity clips were more perceptually ambiguous in emotional meaning than other clips.
Low Medium High Anger 0. Perceptual Differences The results suggest that spontaneous and posed expressions are different — although not necessarily in the way commonly believed. Acoustic Differences Study 2 revealed some further differences between spontaneous and posed expressions regarding acoustic characteristics, although the differences were relatively few, on the whole. Discrete Emotions The results from Study 3 clearly suggest that spontaneous expressions with high emotion intensity conveyed discrete emotions e.
Limitations of the Present Research The above conclusions notwithstanding, there are a number of limitations in the present experiments that should be acknowledged. Implications for Future Research What are the implications of the present study for the use of posed vocal expressions in emotion research in general, and speech databases in particular? Acknowledgements The present research was supported by a grant from the Bank of Sweden Tercentenary Foundation P Aho, K. R package version 1. Google Scholar. Altman, D. Practical statistics for medical research. London: Chapman and Hall.
E-Wiz: A trapper protocol for hunting the expressive speech corpora in lab. Lino et al. Paris: European Language Resources Association. Audibert, N. How we are not all equally competent for discriminating acted from spontaneous expressive speech. Barbosa, S. Reis Eds. Campinas: International Speech Communication Association. Prosodic correlates of acted vs. In Proceedings of Speech Prosody pp. Bachorowski, J. Vocal expression and perception of emotion.
Current Directions in Psychological Science, 8, 53— CrossRef Google Scholar. Vocal expression of emotion: Acoustic properties of speech are associated with emotional intensity and context. Psychological Science, 6, — Banse, R. Acoustic profiles in vocal emotion expression. Journal of Personality and Social Psychology, 70, — Introducing the geneva multimodal expression corpus for experimental research on emotion perception. Emotion, 12, — Barrett, J. Affect-induced changes in speech production. Experimental Brain Research, , — Brunner, E. Box-type approximations in nonparametric factorial designs.
Journal of the American Statistical Association, 92, — Buck, R. Emotion: A biosocial synthesis. Cambridge: Cambridge University Press. Burkhardt, F. A database of German emotional speech. In Proceedings of the 9th European conference on speech communication and technology, Interspeech pp. Lisbon: International Speech Communication Association. Caffi, C. Toward a pragmatics of emotive communication. Journal of Pragmatics, 22, — Carletta, J. Unleashing the killer corpus: Experiences in creating the multi-everything AMI meeting corpus. Language Resources and Evaluation, 41, — Cohen, J.
Statistical power analysis for the behavioral sciences 2nd ed. Mahwah: Erlbaum. Cowie, R. Describing the emotional states that are expressed in speech. Speech Communication, 40, 5— Emotion recognition in human—computer interaction. Cullen, C. Emotional speech corpus construction, annotation, and distribution. Devillers, J. Cowie, E. Batliner Eds. Marrakesh: ELRA. Davitz, J. Auditory correlates of vocal expression of emotional feeling. Davitz Ed. New York: McGraw-Hill. Dinno, A. Multivariate Behavioral Research, 44, — Douglas-Cowie, E.
Emotional speech: Towards a new generation of data bases. Speech Communication, 40, 33— Changing emotional tone in dialogue and its prosodic correlates. Terken Eds. Eindhoven: Eindhoven University. A new emotion database: Considerations, sources, and scope. Belfast: International Speech Communication Association. Paiva, R. Picard Eds. Berlin: Springer. Petta, C. Cowie Eds. Ekman, P.
Should we call it expression or communication? Innovation, 10, — Darwin and facial expression. New York: Academic Press. What is meant by calling emotions basic? Emotion Review, 3, — The repertoire of nonverbal behavior: Categories, origins, usage, and coding. Semiotica, 1, 49— El Ayadi, M.
Classical Indian Dance: Expression of Soul
Survey on speech emotion recognition: Features, classification schemes, and databases. Pattern Recognition, 44, — Eyben, F. Alejandro et al. Barcelona: Association for Computing Machinery. Frank, M. Technical issues in recording nonverbal behavior.
Harrigan, R. Scherer Eds. New York: Oxford University Press. The forced-choice paradigm and the perception of facial expressions of emotion. Journal of Personality and Social Psychology, 80, 75— Frick, R. Communicating emotion: The role of prosodic features. Psychological Bulletin, 97, — Fridlund, A. Human facial expression: An evolutionary view. San Diego: Academic Press. Frommer, J. Calzolari et al. Istanbul: European Language Resources Association. Greasley, P. Emotion in language and speech: Methodological issues in naturalistic settings.
Language and Speech, 43, — Grimm, M. The Vera am Mittag German audio-visual emotional speech database.
- Browse By Tag.
- EL TOQUE DORADO (Spanish Edition).
- The Other Side of Dare (Blessed Trinity)?
- How to Find the Presence of God!
Hansen J. Rhodes: European Speech Communication Association. Haq, S. Speaker-dependent audio-visual emotion recognition.
Harvey Eds. Norwich: International Speech Communication Association. Hawk, S. Emotion, 9, — Izard, C. Organizational and motivational functions of discrete emotions. Haviland Eds. New York: Guilford Press. Effect of acting experience on emotion expression and recognition in voice: Non-actors provide better stimuli than expected. Journal of Nonverbal Behavior, 39, — Authentic and play-acted vocal emotion expressions reveal acoustic differences.
Frontiers in Psychology, 2, Juslin, P. Vocal expression of affect: Promises and problems. Zimmerman Eds. Impact of intended emotion intensity on cue utilization and decoding accuracy in vocal expression of emotion. Emotion, 1, — Communication of emotions in vocal expression and music performance: Different channels, same code? Psychological Bulletin, , — Manuscript submitted for publication. Vocal expression of affect. Kappas, A.
Nonverbal aspects of oral communication. Quasthoff Ed. Berlin: DeGruyter. Kehrein, R. The prosody of authentic emotions. Marlien Eds. Kim, S. Predicting continuous conflict perception with Bayesian Gaussian processes. Klasmeyer, G. Emotional voice variability in speaker verification. Konietschke, F. Journal of Statistical Software, 64, 1— Krahmer, E. On the role of acting skills for the collection of simulated emotional speech. In Proceedings of the international conference on spoken language processing Interspeech Brisbane: Interspeech.
Krebs, J. An introduction to behavioural ecology 3rd ed. Oxford: Blackwell. Laukka, P. Exploring the determinants of the graded structure of vocal emotion expressions. Cognition and Emotion, 26, — Presenting the VENEC corpus: Development of a cross-cultural corpus of vocal emotion expressions and a novel method of annotating emotion appraisals. Devillers, B. Schuller, R. Valletta: European Language Resources Association. Cross-cultural decoding of positive and negative non-linguistic vocalizations. Frontiers in Psychology, 4, Expression of affect in spontaneous speech: Acoustic correlates, perception, and automatic detection of irritation and resignation.
Computer Speech and Language, 25, 84— Levenson, R. Human emotion: A functional view. Davidson Eds. Oxford: Oxford University Press. Martin, O. McKeown, G. Morton, E. On the occurrence and significance of motivation-structural rules in some bird and mammal sounds. American Naturalist, , — Murray, I. Toward the simulation of emotion in synthetic speech: A review of the literature on human vocal emotion. Journal of the Acoustical Society of America, 93, — Neiberg, D. Emotion recognition in spontaneous speech using GMMs. In Proceedings of the 9th international conference on spoken language processing, Interspeech pp.
The time course of emotion recognition in speech and music. Norman, N. Owren, M. Measuring emotion-related vocal acoustics. Allen Eds. Pell, M. Implicit processing of emotional prosody in a foreign versus native language. Speech Communication, 50, — Pittermann, J. Handling emotions in human—computer dialogues. Dordrecht: Springer. Planalp, S. Communicating emotion in everyday life: Cues, channels, and processes. Guerrero Eds. Plutchik, R. The psychology and biology of emotion. Rosenthal, R. Judgment studies: Design, analysis, and meta-analysis.
Russell, J. A circumplex model of affect. Journal of Personality and Social Psychology, 39, — Facial and vocal expressions of emotion. Annual Review of Psychology, 54, — Scheiner, E. Emotion expression—The evolutionary heritage in the human voice. Welsch, W. Wunder Eds. Heidelberg: Springer. Scherer, K. Vocal affect signalling: A comparative approach. Rosenblatt, C. Beer, M. Slater Eds. Vocal affect expression: A review and a model for future research.
Psychological Bulletin, 99, — Vocal markers of emotion: Comparing induction and acting elicitation. Computer Speech and Language, 27, 40— So, 40 hours a week multiplied by 50 weeks a year — accounting for some much-needed vacation time — equals hours. We have hours in a year.
More By Charles Brimmer
If we are lucky, we sleep away hours during that same time. The reality is that many of us spend additional hours thinking about work, contemplating our careers, pondering workplace dynamics and solving problems related to work in our spare time. At the end of the day, a great deal of energy — physical, mental and emotional — is expended in the fulfillment of our work responsibilities.
Work is not meant to be drudgery — something to be avoided and dreaded. We are meant to be active, to contribute, to serve. There is a time for work and a time for rest; a time to produce and a time to play. What if we considered that our chosen vocation was just another opportunity to express the truth of our soul? What if you could actually work in a job that was fulfilling for you — one in which you had a sense of meaning — one where you experienced great joy and excitement? The best way to create the kind of balance we are yearning for is to fully embrace all of who we are and to bring that fully to all that we do — to connect on a soul level.
Think of your soul as the place where your purest self-resides — the truth of who you are at your core — stripped of roles, relationships, and obligations. How can you integrate what you have learned into your vocational life? I realize that these are not necessarily easy questions to answer in a moment or two, unless you have already been exploring this in your life.
Elizabeth Bishop 2 Followers.
Related Expression of Soul
Copyright 2019 - All Right Reserved