A spectral-envelope synthesis model to study perceptual blend between wind instruments
Bibliographic record
Abstract
Wind instrument sounds can be shown to be characterized by pitch-invariant spectral maxima or formants. An acoustical signal-analysis approach is pursued to obtain spectral-envelope descriptions that reveal these pitch- invariant spectral traits. Spectral envelopes are estimated empirically by applying a curve-fitting procedure to a composite distribution of partial-tone frequencies and amplitudes obtained across an instrument’s pitch range. A source-filter synthesis model is designed based on two independent formant filters with their frequency responses matched to the spectral envelope estimates. This is then used in perceptual experiments in which parameter variations of the synthesis filter are manipulated systematically to investigate their contribution to the degree of per- ceived blend between the synthesized sound and a recorded instrument sound. The perceptual relevance is assessed through two tasks in which participants either produce the best attainable blend by directly controlling synthesis parameters or rate the degree of blend for 5 parameter presets. Behavioral data from both experiments suggest the utility of this formant-based model for correlating pitch-invariant acoustical description with perceptual relevance, as both formant frequency and magnitude appear to affect perceived blend.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.000 | 0.001 |
| 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".