Filtering and removal of the effects of the transducers on the acoustical impulse response of concert halls
Bibliographic record
Abstract
Digital signal processing (DSP) has enabled the exponential sine sweep (ESS) method of measuring the acoustical parameters of a concert hall to be increasingly efficient. Part of this is due to the implementation of software modules that perform specific tasks such as filtering and equalization. In using a measurement loudspeaker source for the sine sweep process, it is necessary to: first, derive a loudspeaker prefilter to ensure that the resulting output sweep possesses a frequency response that is reasonably uniform; and second, to derive a transducer inverse filter in order to remove the effects of the loudspeakers and microphones from the measured impulse response of the hall. In the present work, by measuring the acoustical impulse response function (AIRF) of three different halls, using a high-frequency (HF) horn-loaded loudspeaker system as a reference source, it is shown that the effects of the transducers may be effectively filtered and removed from the AIRF.
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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 | 0.000 |
| 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".