The fading of auditory memory
Bibliographic record
Abstract
Due to auditory memory, the auditory system is capable of maintaining a detailed representation of arbitrary waveforms for a period of time, so that a broadband noise and its delayed copies can be perceptually fused. This auditory memory would be critical for perceptually grouping correlated sounds and segregating uncorrelated sounds in noisy, reverberant environments. Its fading process over time was investigated in the present study at the behavioral level, using a break in correlation (BIC, a drop of inter-sound correlation from 1.00 to 0 and then return to 1.00) between two correlated broadband noises. The results show that with the rise of inter-sound delay from 2 to 10 ms under either headphone-stimulation or loudspeaker-stimulation conditions, the shortest BIC duration necessary for listeners to correctly detect the occurrence of the BIC increased rapidly. This elevation in the duration threshold was faster under the headphone-stimulation condition than the loudspeaker-stimulation condition. Also, the listeners reaction time in response to the BIC but not that to a comparable silent gap elongated quickly with the increase in the inter-sound delay from 1 to 8 ms. Thus the auditory memory of fine structures fades rapidly after the sound waves are received. [Work supported by MSTC and NSERCC.]
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".