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Age and Culture Effects on the Ability to Decode Affect Bursts

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Book cover Quantifying and Processing Biomedical and Behavioral Signals (WIRN 2017 2017)

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Abstract

This paper investigates the ability of adolescents (aged 13–15 years) and young adults (aged 20–26 years) to decode affective bursts culturally situated in a different context (Francophone vs. South Italian). The effects of context show that Italian subjects perform poorly with respect to the Francophone ones revealing a significant native speaker advantage in decoding the selected affective bursts. In addition, adolescents perform better than young adults, particularly in the decoding and intensity ratings of affective bursts of happiness, pain, and pleasure suggesting an effect of age related to language expertise.

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Notes

  1. 1.

    See vnl.psy.gla.ac.uk/resources.php (last verified—January 2018). In particular, see: vnl.psy.gla.ac.uk/sounds/ and search for Montreal_Affective_Voices.zip (last verified—January 2018).

References

  1. Belin, P., Fillion-Bilodeau, S., Gosselin, F.: The Montreal Affective Voices: a validated set of nonverbal affect bursts for research on auditory affective processing. Behav. Res. Methods 40(2), 531–539 (2008)

    Article  Google Scholar 

  2. Ekman, P.: Emotions Revealed: Recognizing Faces and Feelings to Improve Communication and Emotional Life. Weidenfeld and Nicolson, London (2003)

    Google Scholar 

  3. Esposito, A., Jain, L.C.: Modeling social signals and contexts in robotic socially believable behaving systems. In: Esposito, A., Jain, L.C. (eds.) Toward Robotic Socially Believable Behaving Systems Volume II—“Modeling Social Signals”. ISRL Series, vol. 106, pp. 5–13. Springer International Publishing Switzerland (2016)

    Google Scholar 

  4. Esposito, A., Esposito, A.M., Vogel, C.: Needs and challenges in human computer interaction for processing social emotional information. Pattern Recogn. Lett. 66, 41–51 (2015)

    Article  Google Scholar 

  5. Esposito, A., Esposito, A.M.: On the recognition of emotional vocal expressions: motivations for an holistic approach. Cogn. Process. J. 13(2), 541–550 (2012)

    Article  Google Scholar 

  6. Jack, R.E., Schyns, P.G.: The human face as a dynamic tool for social communication. Curr. Biol. 25(14), R621–R634 (2015)

    Article  Google Scholar 

  7. Maldonato, N.M., Dell’Orco, S.: Making decision under uncertainty, emotions, risk and biases. In: Bassis, S., Esposito, A., Morabito, F.C. (eds.) Advances in Neural Networks: Computational and Theoretical Issues. SIST Series, vol. 37, pp. 293–302. Springer International Publishing Switzerland (2015)

    Google Scholar 

  8. Matsumoto, D., Nezlek, J.B., Koopmann, B.: Evidence for universality in phenomenological emotion response system coherence. Emotion 7(1), 57–67 (2007)

    Article  Google Scholar 

  9. Riviello, M.T., Esposito, A.: On the Perception of Dynamic Emotional Expressions: A Cross-Cultural Comparison. In: Hussain, A. (ed.) SpringerBriefs in Cognitive Computation, vol. 6, pp. 1–45 (2016)

    Google Scholar 

  10. Sauter, D., Eisner, F., Ekman, P., Scott, S.K.: Perceptual cues in non-verbal vocal expressions of emotion. Q. J. Exp. Psychol. (Hove) 63(11), 2251–2272 (2010)

    Article  Google Scholar 

  11. Sauter, D., Eisner, F., Ekman, P., Scott, S.K.: Cross-cultural recognition of basic emotions through nonverbal emotional vocalizations. PNAS 107(6), 2408–2412 (2010)

    Article  Google Scholar 

  12. Scherer, K.R., Banse, R., Wallbott, H.C.: Emotion inferences from vocal expression correlate across languages and cultures. J. Cross Cult. Psychol. 32(1), 76–92 (2007)

    Article  Google Scholar 

  13. Schröder, M.: Experimental study of affect bursts. Speech Commun. 40, 99–116 (2003)

    Article  Google Scholar 

  14. Troncone, A., Palumbo, D., Esposito, A.: Mood effects on the decoding of emotional voices. In: Bassis, S., et al. (eds.) Recent Advances of Neural Network Models and Applications. SIST, vol. 26, pp. 325–332. International Publishing Switzerland (2014)

    Google Scholar 

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Acknowledgements

The research leading to the results presented in this paper has been conducted in the project EMPATHIC (Grant No.: 769872) that received funding from the European Union’s Horizon 2020 research and innovation programme. The dean and the ethical committee of the “Francesco Durante” school situated in Frattamaggiore, Napoli, Italy are acknowledged for allowing the data collection. Acknowledgements are also due to parents, adolescents, and young adults participating to the experiment.

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Correspondence to Anna Esposito .

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Esposito, A., Esposito, A.M., Scibelli, F., Maldonato, M.N., Vogel, C. (2019). Age and Culture Effects on the Ability to Decode Affect Bursts. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Quantifying and Processing Biomedical and Behavioral Signals. WIRN 2017 2017. Smart Innovation, Systems and Technologies, vol 103. Springer, Cham. https://doi.org/10.1007/978-3-319-95095-2_3

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