Comparing the binaural recordings of 22.2- and 2-channel music reproduced in three listening rooms
Bibliographic record
Abstract
A room interacts with sound sources. It alters both timbral and spatial impression of produced and reproduced sound field(s), and affects the overall sonic experiences. In this study, we approached the room-induced effect in the context of an immersive audio rendering, and investigated a relationship between room acoustics and audio reproduction formats. First, three classical music pieces were recorded and mixed optimally for the 22.2- and 2-channel reproduction formats. Subsequently, we generated a set of binaural responses to each of 22.2- and 2-channel reproduced music at three distinct listening rooms (varying dimensions and reflecting surfaces). Eleven listeners participated in a listening experiment; they compared two randomly selected binaural stimuli and rated perceived dissimilarity. The collected ratings were analyzed through the individual differential scaling (INDSCAL) to determine a perceptual space of the stimuli. The results show that (1) the listeners perceived the stimuli differences through two factors-the reproduction format (dimension 1) and the listening room (dimension 2); and (2) the room-induced perceptual difference was less dominant for the listeners compared to the format-induced one. The importance of each dimension was determined via the goodness of fit of the INDSCAL results as follows: Dimension 1-0.7138 and Dimension 2-0.1649.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".