Acoustic imaging of string instrument soundboxes
Bibliographic record
Abstract
A circular 30-microphone array of 90 cm radius has been used to produce acoustic images of several string instruments. The soundboxes were excited by an automated impact hammer, and the instruments were suspended inside the array in such a manner that both the soundbox and hammer mechanism could be rotated in the horizontal plane. By normalizing all microphone signals to the hammer signal, data could be assembled as if from an array of many times 30 microphones. Images were formed using the inverse frequency response function method. The array and data analysis code were tested with a rectangular plate set in a large plywood baffle, a system that was straightforward to simulate numerically. Due to the limited spatial resolution set by the array geometry and frequency range - typically 200-1000 Hz - instruments with long soundboxes were chosen for initial testing: a gothic harp, a guzheng and a guqin.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".