IEMOCAP: interactive emotional dyadic motion capture database

IEMOCAP: interactive emotional dyadic motion capture database

Since emotions are expressed through a combination of verbal and non-verbal channels, a joint analysis of speech and gestures is required to understand expressive human communication. To facilitate such investigations, this paper describes a new corpus named the "interactive emotional dyadic mo...

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Bibliographic Details
Published in:Language Resources and Evaluation Vol. 42; no. 4; pp. 335 - 359
Main Authors: Busso, Carlos, Bulut, Murtaza, Lee, Chi-Chun, Kazemzadeh, Abe, Mower, Emily, Kim, Samuel, Chang, Jeannette N., Lee, Sungbok, Narayanan, Shrikanth S.
Format: Journal Article
Language:English
Published: Dordrecht Springer 01-12-2008
Springer Netherlands
Springer Nature B.V
Subjects:
Anger
Applied linguistics
Communication
Communication research
Computational Linguistics
Computer Science
Corpus analysis
Database design
Dyadics
Emotional expression
Emotional states
Emotions
Face (Body)
Facial expressions
Frustration
Gestures
Hands
Happiness
Human communication
Language and Literature
Linguistics
Motion
Motion perception
Nonverbal communication
Sadness
Social Sciences
United States > US
Germany
Motion capture system
Audio-visual database
Dyadic interaction
Emotion
Emotional assessment
Corpus linguistics
Database
Communication
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Summary:Since emotions are expressed through a combination of verbal and non-verbal channels, a joint analysis of speech and gestures is required to understand expressive human communication. To facilitate such investigations, this paper describes a new corpus named the "interactive emotional dyadic motion capture database" (IEMOCAP), collected by the Speech Analysis and Interpretation Laboratory (SAIL) at the University of Southern California (USC). This database was recorded from ten actors in dyadic sessions with markers on the face, head, and hands, which provide detailed information about their facial expressions and hand movements during scripted and spontaneous spoken communication scenarios. The actors performed selected emotional scripts and also improvised hypothetical scenarios designed to elicit specific types of emotions (happiness, anger, sadness, frustration and neutral state). The corpus contains approximately 12 h of data. The detailed motion capture information, the interactive setting to elicit authentic emotions, and the size of the database make this corpus a valuable addition to the existing databases in the community for the study and modeling of multimodal and expressive human communication.
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ISSN:1574-020X
1572-8412
1574-0218
DOI:10.1007/s10579-008-9076-6