Title
Using Expressive Avatars to Increase Emotion Recognition: A Pilot Study
Abstract
BSTRACT Virtual avatars are widely used for collaborating in virtual environments. Yet, often these avatars lack expressiveness to determine a state of mind. Prior work has demonstrated effective usage of determining emotions and animated lip movement through analyzing mere audio tracks of spoken words. To provide this information on a virtual avatar, we created a natural audio data set consisting of 17 audio files from which we then extracted the underlying emotion and lip movement. To conduct a pilot study, we developed a prototypical system that displays the extracted visual parameters and then maps them on a virtual avatar while playing the corresponding audio file. We tested the system with 5 participants in two conditions: (i) while seeing the virtual avatar only an audio file was played. (ii) In addition to the audio file, the extracted facial visual parameters were displayed on the virtual avatar. Our results suggest the validity of using additional visual parameters in the avatars’ face as it helps to determine emotions. We conclude with a brief discussion on the outcomes and their implications on future work.
Year
DOI
Venue
2022
10.1145/3491101.3519822
Conference on Human Factors in Computing Systems
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Natalie Hube100.34
Kresimir Vidackovic200.34
Michael Sedlmair391551.74