Microphone array measurement system for analysis of directional and spatial variations of sound fields
Bibliographic record
Abstract
A measurement system has been developed that is capable of analyzing the directional and spatial variations in a reverberant sound field. A spherical, 32-element array of microphones is used to generate a narrow beam that is steered in 60 directions. Using an omnidirectional loudspeaker as excitation, the sound pressure arriving from each steering direction is measured as a function of time, in the form of pressure impulse responses. By subsequent analysis of these responses, the variation of arriving energy with direction is studied. The directional diffusion and directivity index of the arriving sound can be computed, as can the energy decay rate in each direction. An analysis of the 32 microphone responses themselves allows computation of the point-to-point variation of reverberation time and of sound pressure level, as well as the spatial cross-correlation coefficient, over the extent of the array. The system has been validated in simple sound fields in an anechoic chamber and in a reverberation chamber. The system characterizes these sound fields as expected, both quantitatively from the measures and qualitatively from plots of the arriving energy versus direction. It is anticipated that the system will be of value in evaluating the directional distribution of arriving energy and the degree and diffuseness of sound fields in rooms.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".