SPATIAL AUDITORY DISPLAY USING MULTIPLE SUBWOOFERS IN TWO DIFFERENT REVERBERANT REPRODUCTION ENVIRONMENTS
Bibliographic record
Abstract
Spatial auditory displays that use multichannel loudspeaker arrays in reverberant reproduction environments often use single subwoofers to reproduce all the low frequency content to be presented to the listener, consistent with consumer home theater practices. However, even in small reverberant listening rooms, such as those of the typical home theater, it is possible to display a greater variety of clear distinctions in resulting spatial auditory imagery when using laterally positioned subwoofers to present two different signals. This study investigated listeners’ ability to discriminate between correlated and decorrelated low-frequency audio signals, emanating from multiple subwoofers located in two different reverberant environments, characterized as “home” versus “lab.” Octave-band noise samples, with center frequencies ranging in third-octave steps from 40 Hz to 100 Hz, were presented via a pair of subwoofers poitioned relative to the listener either in a left-right (LR) orientation, or in a front-back (FB) orientation. When delivered via subwoofers in the FB orientation, in each of the two reproduction envirnoments, discrimination between correlated and decorrelated low-frequency signals was at chance levels (i.e., the discrimination was effectively impossible). When delivered via the laterally positioned subwoofers (orientation LR) in the acoustically-controlled laboratory environment, the signals could be perfectly and easily discriminated. In constrast, when tests were run in the small and highly reverberant (i.e., home) environment, the decorrelated signals were not so easily distinguished from those that were correlated at the subwoofers, with performance gradually falling to chance levels as the center frequency of the stimulus was decreased below 50 Hz.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".