The Acoustic Properties of Affective Timbres: Consistencies and Discrepancies in a Synthesis of Multiple Datasets
Bibliographic record
Abstract
In the investigation of musical features that influence musical affect, timbre has received relatively little attention. We studied the acoustic properties describing the timbral qualities of sound and analyzed how they predict perceived and induced affect. First, we considered the timbre of single tones played by different instruments by re-analyzing two previously published studies on perceived affect by Eerola et al. (2012, Mus. Percept.) and McAdams et al. (2017, Front. Psychol.) and comparing them to Experiment 1 from Korsmit et al. (2023, submitted), which investigated both perceived and induced affect on valence, tension arousal, and energy arousal ratings. For all datasets, positive valence and decreased tension were predicted by an increasingly prominent fundamental frequency. In experiments with pitch variation, energy arousal was predicted by increased pitch and decreased inharmonicity. In experiments with variations in playing technique, energy arousal was predicted by a faster attack or less sustain. Second, we compared Experiment 1 results on dimensional affect (valence, tension, energy) to results on discrete affect (anger, fear, sadness, happiness, tenderness). Like valence and tension, angrier and more fearful sounds and less happy and tender sounds showed a less prominent fundamental frequency. Happiness and tenderness had a shorter perceived duration, and sad sounds were more sustained. Third, Experiment 2 from Korsmit et al. (2023) tested the affective response to chromatic scales. As with single tones, energy was predicted by an increase in pitch and decrease in inharmonicity. However, dimensional and discrete affect were most frequently predicted by median inharmonicity and spectral spread range. The synthesis of multiple datasets revealed consistent findings, but also discrepancies that may be explained by differences in stimulus selection. Furthermore, although findings on perceived and induced affect were largely similar, some findings on discrete affect and chromatic scales were not revealed with dimensional affect and single tones.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".