A-VB Two
2 papers with code • 1 benchmarks • 1 datasets
In the A-VB Two track, we investigate a low-dimensional emotion space that is based on the circumplex model of affect. Participants will predict values of arousal and valence (on a scale from 1=unpleasant/subdued, 5=neutral, 9=pleasant/stimulated) as a regression task. Participants will report the average Concordance Correlation Coefficient (CCC), as well as the Pearson correlation coefficient, across the two dimensions. The baseline for this challenge will be based on CCC.
Benchmarks
These leaderboards are used to track progress in A-VB Two
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HUME-VB
Most implemented papers
The ACII 2022 Affective Vocal Bursts Workshop & Competition: Understanding a critically understudied modality of emotional expression
The ACII Affective Vocal Bursts Workshop & Competition is focused on understanding multiple affective dimensions of vocal bursts: laughs, gasps, cries, screams, and many other non-linguistic vocalizations central to the expression of emotion and to human communication more generally.
A Hierarchical Regression Chain Framework for Affective Vocal Burst Recognition
JinchaoLove/AffectiveVocalBurstRecognition
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Experimental results based on the ACII Challenge 2022 dataset demonstrate the superior performance of the proposed system and the effectiveness of considering multiple relationships using hierarchical regression chain models.
