Title
The OMG-Empathy Dataset: Evaluating the Impact of Affective Behavior in Storytelling
Abstract
Processing human affective behavior is important for developing intelligent agents that interact with humans in complex interaction scenarios. A large number of current approaches that address this problem focus on classifying emotion expressions by grouping them into known categories. Such strategies neglect, among other aspects, the impact of the affective responses from an individual on their interaction partner thus ignoring how people empathize towards each other. This is also reflected in the datasets used to train models for affective processing tasks. Most of the recent datasets, in particular, the ones which capture natural interactions (“in-the-wild” datasets), are designed, collected, and annotated based on the recognition of displayed affective reactions, ignoring how these displayed or expressed emotions are perceived. In this paper, we propose a novel dataset composed of dyadic interactions designed, collected and annotated with a focus on measuring the affective impact that eight different stories have on the listener. Each video of the dataset contains around 5 minutes of interaction where a speaker tells a story to a listener. After each interaction, the listener annotated, using a valence scale, how the story impacted their affective state, reflecting how they empathized with the speaker as well as the story. We also propose different evaluation protocols and a baseline that encourages participation in the advancement of the field of artificial empathy and emotion contagion.
Year
DOI
Venue
2019
10.1109/ACII.2019.8925530
2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)
Keywords
Field
DocType
Empathy,Dyadic Interactions,Affective Behaviour
Empathy,Social psychology,Intelligent agent,Storytelling,Expression (mathematics),Affective behavior,Task analysis,Computer science,Cognitive psychology,Neglect,Affect (psychology)
Conference
ISSN
ISBN
Citations 
2156-8103
978-1-7281-3889-3
0
PageRank 
References 
Authors
0.34
20
4
Name
Order
Citations
PageRank
Pablo V. A. Barros111922.02
Nikhil Churamani200.34
Angelica Lim313.06
Stefan Wermter41100151.62