Cancellation of room reflections over an extended area using Ambisonics
Bibliographic record
Abstract
This paper investigates the compensation of room reflections based on Ambisonics. A multichannel room equalization method for Ambisonic playback systems is proposed. The compensation filters are designed to operate in the spherical harmonics domain, prior to the decoding step. Their design requires the inversion of a matrix which can be ill-conditioned at low frequencies and for higher Ambisonic orders. A crossover and cross-order method is proposed to circumvent this problem and to reduce the amount of necessary regularization. Simulation results are presented in frequency, space, and temporal domains over a wide-range of frequencies. It is shown that the proposed method is efficient and can reduce the reproduction error to -14 dB in the reconstruction area defined in free field. Practical considerations such as Ambisonic room response estimation and robustness of the method are investigated. Experimental results are provided and show good agreement with the theory. Finally, a glimpse into the extension of the proposed method to create three-dimensional measurement-based Ambisonic reverberation is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".