The “Musical Emotional Bursts”: a validated set of musical affect bursts to investigate auditory affective processing
Bibliographic record
Abstract
The Musical Emotional Bursts (MEB) consist of 80 brief musical executions expressing basic emotional states (happiness, sadness and fear) and neutrality. These musical bursts were designed to be the musical analog of the Montreal Affective Voices (MAV)-a set of brief non-verbal affective vocalizations portraying different basic emotions. The MEB consist of short (mean duration: 1.6 s) improvisations on a given emotion or of imitations of a given MAV stimulus, played on a violin (10 stimuli × 4 [3 emotions + neutral]), or a clarinet (10 stimuli × 4 [3 emotions + neutral]). The MEB arguably represent a primitive form of music emotional expression, just like the MAV represent a primitive form of vocal, non-linguistic emotional expression. To create the MEB, stimuli were recorded from 10 violinists and 10 clarinetists, and then evaluated by 60 participants. Participants evaluated 240 stimuli [30 stimuli × 4 (3 emotions + neutral) × 2 instruments] by performing either a forced-choice emotion categorization task, a valence rating task or an arousal rating task (20 subjects per task); 40 MAVs were also used in the same session with similar task instructions. Recognition accuracy of emotional categories expressed by the MEB (n:80) was lower than for the MAVs but still very high with an average percent correct recognition score of 80.4%. Highest recognition accuracies were obtained for happy clarinet (92.0%) and fearful or sad violin (88.0% each) MEB stimuli. The MEB can be used to compare the cerebral processing of emotional expressions in music and vocal communication, or used for testing affective perception in patients with communication problems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".