Acoustic Structure and Musical Function: Musical Notes Informing Auditory Research
Bibliographic record
Abstract
Music’s continual temporal changes make it a useful stimulus for studying cognitive and neural processes unfolding over time. Although this dynamic nature is widely recognized on a macro level, the importance of temporal changes in individual notes is less widely discussed. For example, textbooks often focus on power spectra—time invariant summaries of spectral information—to explain differences in timbre between musical instruments. Unfortunately, this approach overlooks the importance of dynamic fluctuations in individual notes’ overtones. This chapter highlights the under-recognized importance of temporal structure in musical sounds by synthesizing a diverse range of research on musical acoustics and perception. It concludes by contrasting the rich temporal dynamics of musical sounds with the temporally invariant tones common in auditory perception research—which exhibit significant shortcomings regarding ecological validity. Although this creates barriers for generalizing outcomes from experiments with simplistic tones, it also offers exciting new topics for future research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.003 |
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; both teacher heads agree on what is shown here.
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".