In-room sound reproduction using active control: Simulations in the frequency domain and comparison with wave field synthesis
Bibliographic record
Abstract
Active sound control simulations were performed for progressive sound field reproduction over a ‘‘large’’ area using multiple monopole loudspeakers. The model is limited to the simulation of the acoustical output of the prescribed loudspeaker array in a simple room, and is based on achieving an optimal control in the frequency domain. This rather simple approach is chosen for this first feasibility study concerning a limited number of possible configurations of sensing microphones and loudspeakers. Other issues of interest concern the comparison with wave field synthesis, the control mechanisms and transducer configurations. As it is demonstrated, in-room reproduction of sound field using active control can be achieved with a residual normalized squared error below 2% while open-loop wave field synthesis gives more than 100% of error in the same situation. Usage of active control technique suggests the possibility to automatically overcome the room’s natural dynamics. A special surrounding configuration of sensors is introduced for a sensor-free listening area. [Work supported by NSERC, NATEQ, VRQ, and Université de Sherbrooke.]
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".