A new active acoustics system for enhancing musician's environment on concert and recording stages
Bibliographic record
Abstract
The necessity of variable acoustics in modern performance spaces is widely acknowledged; particularly, there has been a growing interest in active acoustics enhancement systems. Many different systems have been developed and installed in concert halls, public venues, and research facilities worldwide. However, further improvements are required to provide musicians with a desirable acoustic on-stage support equal in quality to the best rooms. An innovative electro-acoustic enhancement system, based on measured high-resolution impulse responses, is developed at the Virtual Acoustics Technology (VAT) lab, in McGill University. The first model is installed in Multi-Media Room (MMR), a large rectangular space (80 ft. × 60 ft. × 50 ft.) designed as a film scoring stage. The system uses an array of omni-directional radiators and its signal processing includes 24-channel low-latency convolution at 24 bit/96 KHz, three separate stages of matrix mixing, equalization, and time variation. The objective measurement of the system adjusted to improve on-stage acoustics verifies the enhancement of parameters such as inter-aural cross-correlation coefficient (IACC), early stage support (ST1), and early decay time (EDT) without excessively increasing the overall acoustic energy in the room. The subjective evaluations collected from multiple recording sessions with professional musicians using the system will be presented. [Work supported by NSERC, JMP.]
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".