Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Acoustic profiles in vocal emotion expression

R Banse1, K R Scherer

  • 1Department of Psychology, Humboldt University, Berlin, Germany.

Journal of Personality and Social Psychology
|March 1, 1996
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Promotion of mental health in young adults via mobile phone app: study protocol of the ECoWeB (emotional competence for well-being in Young adults) cohort multiple randomised trials.

BMC psychiatry·2020
Same author

Perceived gesture dynamics in nonverbal expression of emotion.

Perception·2014
Same author

Minimal cues in the vocal communication of affect: Judging emotions from content-masked speech.

Journal of psycholinguistic research·2013
Same author

Implicit attitudes towards homosexuality: reliability, validity, and controllability of the IAT.

Zeitschrift fur experimentelle Psychologie : Organ der Deutschen Gesellschaft fur Psychologie·2001
Same author

Attitude measurement using the Implicit Association Test (IAT).

Zeitschrift fur experimentelle Psychologie : Organ der Deutschen Gesellschaft fur Psychologie·2001
Same author

Studying the dynamics of emotional expression using synthesized facial muscle movements.

Journal of personality and social psychology·2000
Same journal

Outgroup friendships and social influence in the development of adolescent attitudes toward secondary outgroups.

Journal of personality and social psychology·2026
Same journal

The impact of "relational" Artificial Intelligence on human well-being: A self-determination theory analysis.

Journal of personality and social psychology·2026
Same journal

Is my loneliness killing me? Effects of loneliness and social isolation on transitions between cognitive status categories and death.

Journal of personality and social psychology·2026
Same journal

Listening across the divide: High-quality listening promotes speakers' state well-being through basic psychological need satisfaction during disagreements.

Journal of personality and social psychology·2026
Same journal

Morality cut both ways: The role of cognition and emotion in attitude moralization and demoralization.

Journal of personality and social psychology·2026
Same journal

The predictive validity of vocational interests for life outcomes across adulthood.

Journal of personality and social psychology·2026
See all related articles

Judges can accurately decode emotions from actors' vocal expressions, with specific vocal parameters correlating to emotion intensity and valence. Acoustic analysis confirms these vocal patterns align with the component process model of emotion.

Area of Science:

  • Psychology
  • Acoustic Phonetics
  • Nonverbal Communication

Background:

  • Vocal emotion recognition is crucial for social interaction.
  • Previous research indicates better-than-chance accuracy in decoding vocal emotions.
  • Understanding the acoustic features of emotional speech is an ongoing area of research.

Purpose of the Study:

  • To investigate the accuracy of vocal emotion decoding by human judges.
  • To analyze the acoustic parameters of acted emotional speech.
  • To test the component process model of emotion (CPME) regarding vocal expression.

Main Methods:

  • Professional actors portrayed 14 emotions of varying intensity and valence.
  • Judges evaluated the emotional content of the portrayals.

Related Experiment Videos

  • Digital acoustic analysis was performed on 224 vocalizations to extract vocal parameters.
  • Statistical analyses, including discriminant analysis and jackknifing, were employed.

    • Main Results:

    • Judges demonstrated significantly better-than-chance accuracy in decoding expressed emotions.
    • Consistent differences in the recognizability of various emotions were observed.
    • Acoustic parameters were found to correlate with both the intensity and valence of emotions.
    • Vocal patterns largely supported the CPME, with some hypotheses requiring revision.

    Conclusions:

    • Vocal cues provide reliable information for emotion recognition.
    • Specific acoustic features are systematically related to emotional states.
    • The findings support and refine the component process model of emotion based on empirical vocal data.