Opening book details…
Can I read CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset on EtoBox?
CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset by Houwei Cao; David G. Cooper; Michael K. Keutmann; Ruben C. Gur; Ani Nenkova; Ragini Verma is a Psychology article available to read on EtoBox.
What is CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset about?
People convey their emotional state in their face and voice. We present an audio-visual dataset uniquely suited for the study of multi-modal emotion expression and perception. The dataset consists of facial and vocal emotional expressions in sentences spoken in a range of basic emotional states (happy, sad, anger, fear, disgust, and neutral). 7,442 clips of 91 actors with diverse ethnic backgrounds were rated by multiple raters in three modalities: audio, visual, and audio-visual. Categorical emotion labels and real-value intensity values for the perceived emotion were collected using crowd-sourcing from 2,443 raters. The human recognition of intended emotion for the audio-only, visual-only, and audio-visual data are 40.9, 58.2 and 63.6 percent respectively. Recognition rates are highest for neutral, followed by happy, anger, disgust, fear, and sad. Average intensity levels of emotion are rated highest for visual-only perception. The accurate recognition of disgust and fear requires simultaneous audio-visual cues, while anger and happiness can be well recognized based on evidence from a single modality. The large dataset we introduce can be used to probe other questions concerning
Who reads CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset?
It is typically read by researchers, students, and practitioners in Psychology.
- Author
- Houwei Cao; David G. Cooper; Michael K. Keutmann; Ruben C. Gur; Ani Nenkova; Ragini Verma
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Published
- 2014
- Language
- EN
- Field
- Psychology (Social Sciences)