Anechoic measurements of particle-velocity probes compared to pressure gradient and pressure microphones
Bibliographic record
Abstract
The Microflown is an acoustic particle velocity sensor invented at the University of Twente in Holland in 1994 and commercialized in 1997 [1, 9]. The sensor directly measures particle velocity rather than pressure-gradient as do most unidirectional and bidirectional microphones. The sensor has several interesting operational characteristics however few measurements of the Microflown have been published until now making it difficult for a potential user to assess the merits of this transducer in comparison to high quality condenser microphones commonly used in music and speech recording. This paper offers some insight by presenting anechoic measurements of particle velocity probes compared to the measurements of pressure-gradient and pressure microphones (of condenser type) made under identical acoustical conditions at varying distances from a point source having a wide frequency range. Detailed frequency response measurements show how the characteristics of these transducer types are dependent on their distance to the source, and highlight the need of transducer calibration with respect to distance. Very few microphone manufacturers publish frequency response data for more than one reference distance to the source although distance is often used to modify the applied response of the microphone. An additional goal for making these measurements is to establish the relationship between particle velocity and pressure gradient values using the same acoustical conditions. The measurements were made in the large anechoic chamber of the NHK Science and Technical Research Laboratories (STRL) in Tokyo during the April-May of 2006.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".