audEERING's approach to the One-Minute-Gradual Emotion Challenge
Andreas Triantafyllopoulos, Hesam Sagha, Florian Eyben, Bj\"orn, Schuller
TL;DR
This paper details audEERING's submissions and evaluations for the One-Minute-Gradual emotion recognition challenge, focusing on audio and video processing to predict arousal and valence with specific CCC scores.
Contribution
The paper introduces audEERING's approach and results in the OMG emotion recognition challenge, including evaluation metrics for audio and video modalities.
Findings
Achieved 0.343 CCC for arousal from audio
Achieved 0.401 CCC for valence from video
Provided detailed evaluation results for subject-dependent assessments
Abstract
This paper describes audEERING's submissions as well as additional evaluations for the One-Minute-Gradual (OMG) emotion recognition challenge. We provide the results for audio and video processing on subject (in)dependent evaluations. On the provided Development set, we achieved 0.343 Concordance Correlation Coefficient (CCC) for arousal (from audio) and .401 for valence (from video).
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Taxonomy
TopicsEmotion and Mood Recognition · Speech and Audio Processing · Speech Recognition and Synthesis