Vibration Sensitivity of One-Port and Two-Port MEMS Microphones
Bibliographic record
Abstract
Micro-electromechanical system (MEMS) microphones (mics) with two acoustic ports are currently receiving considerable interest, with the promise of achieving higher directional sensitivity compared to traditional one-port architectures. However, measuring pressure differences in two-port microphones typically commands sensing elements that are softer than in one-port mics and are therefore presumably more prone to interference from external vibration. Here, we derive a universal expression for microphone sensitivity to vibration, and we experimentally demonstrate its validity for several emerging two-port microphone technologies. We also perform vibration measurements on a one-port mic, thus providing a one-stop direct comparison between one-port and two-port sensing approaches. We find that the acoustically-referred vibration sensitivity of two-port MEMS mics, in units of measured acoustic pressure per external acceleration (i.e., Pascals per g), does not depend on the sensing element stiffness nor on its natural frequency. We also show that this vibration sensitivity in two-port mics is inversely proportional to frequency (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${S}_{\text {Pa}/{g}}\propto {1}/{f}$ </tex-math></inline-formula>) as opposed to the frequency independent behavior observed in one-port mics. This is confirmed experimentally for several types of microphone packages.
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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 | 0.000 | 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".