An alternative solution for positioning sound sources in loudspeaker-based virtual environments
Bibliographic record
Abstract
In auditory virtual environments it is often required to position an anechoic point source in three-dimensional space. When sources in such applications are to be displayed using multichannel loudspeaker reproduction systems, the processing is typically based upon simple amplitude-panning laws. This paper describes an alternative approach based on an array of virtual microphones. The aim of the system architecture design was to comply with the expectations of audio engineers and to create sound imagery similar to those associated with standard sound recording practice. In the newly designed environment, the microphones, with adjustable directivity patterns and axis orientations, can be spatially placed as desired. This way, time-delay panning can be included by simulating a non-coincident microphone array. By the use of omnidirectional microphones the panning is almost solely based on time-delay panning and thus performance can take advantage of the precedence effect. Also, the proposed architecture is flexible enough to include classic amplitude panning laws by translating the requested panning law into physically non-existing microphone directivity patterns. Moreover, the virtual directivity patterns do not have to be rotationally symmetrical. [Work supported by VRQ.]
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".