Papers › Evaluating Variants of wav2vec 2.0 on Affective Vocal Burst Tasks
Evaluating Variants of wav2vec 2.0 on Affective Vocal Burst Tasks
Bagus Tris Atmaja, Akira Sasou
The search for emotional biomarkers within the human voice is a challenging research area. Previous studies focused on predicting affective state from speech; this study explores various tasks on affective vocal bursts. Borrowing the success of self-supervised learning in automatic speech recognition, we extracted acoustic embedding using variants of wav2vec 2.0 for four affective vocal bursts tasks: High, Two, Culture, and Type. Using a similar architecture for all tasks, the evaluation of acoustic embeddings reveals the potential use of wav2vec 2.0 variants over the conventional acoustic features in affective vocal bursts tasks. We evaluated both conventional acoustic features and these acoustic embeddings on the different number of twenty seeds evaluation and reported the maximum and average scores with their standard deviations in the validation set. Three high scores from these validations for all tasks assist the generation of predictions for the test set. We compared the test scores with previous studies and obtained remarkable improvements.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Cultural Vocal Bursts Intensity Prediction | HUME-VB | w2v2-r-er | Concordance correlation coefficient (CCC) | 0.5199 | #2 of 2 | Archive leaderboard | report |
| Vocal Bursts Intensity Prediction | HUME-VB | w2v2-r-vad | Concordance correlation coefficient (CCC) | 0.6554 | #2 of 2 | Archive leaderboard | report |
| Vocal Bursts Type Prediction | HUME-VB | w2v2-r-er | Average Recall | 0.4902 | #1 of 1 | Archive leaderboard | report |
| Vocal Bursts Valence Prediction | HUME-VB | w2v2-r-er | Concordance correlation coefficient (CCC) | 0.6290 | #1 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections