The Acoustic Properties of Affective Timbres: Consistencies and Discrepancies in a Synthesis of Multiple Datasets
Why this work is in the frame
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Bibliographic record
Abstract
In the investigation of musical features that influence musical affect, timbre has received relatively little attention. Investigating affective timbres as they vary between instrument families can lead to inconsistent results, because one instrument family can produce a wide variety of timbres. Here, we consider timbre descriptors, as fine-grained acoustic representations of a sound. Using identical methods, we re-analyzed and synthesized results from three previously published studies: Eerola et al. (2012, Mus. Percept.), McAdams et al. (2017, Front. Psychol.), and Korsmit et al. (2023, Front. Psychol.). In doing so, we aimed to reveal robust timbre descriptors that consistently predict the affective response and to explain any discrepancies in results arising from differences in experimental methodology. We computed spectral, temporal, and spectro-temporal descriptors from all stimuli and used these to predict the affect ratings using linear and nonlinear methods. Our most consistent finding was that the fundamental frequency or higher-frequency energy of a sound predicted pleasant affect (i.e., positive valence, happiness, sadness) in one direction and unpleasant affect (i.e., tension, anger, fear) in the opposite direction. Clear discrepancies in previous findings may be attributable to differences in experimental design. When pitch variation was present in a stimulus set, energy arousal was predicted by pitch and inharmonicity, whereas when attack variation was present in the stimulus set, energy arousal was predicted by a faster attack and shorter sustain.
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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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it