Acoustic noise suppression using regressive adaptive filtering
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Experimental field tests dealing with the background acoustic noise in cars under various driving conditions are described. Analysis reveals that there is a high correlation between the acoustic noise in the area facing the driver's seat and the noise in other locations in the car, which suggests the possibility of using the two-microphones noise cancellation approach. Results show that using a conventional finite-impulse response adaptive filter with the stochastic gradient adaptation algorithm leads to up to 12 dB of noise cancellation in the low end of the noise spectrum; some noise enhancement was noticed at the high end of the spectrum. This problem is discussed, along with a possible solution approach using proper filtering. A limitation of the two-microphones cancellation is that the optimal location of the secondary microphone varies, depending on the driving conditions. A multiple secondary microphones scheme is proposed as a solution. This scheme resulted in further reductions of the residual noise.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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) | 0.001 | 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 it