Bidirectional decay of auditory memory traces for pitch in speech sounds
Bibliographic record
Abstract
Previous studies have shown human listeners have greater detection sensitivity to pitch increment than decrement in successive sounds. Assuming deviance detection is based on the comparison between the memory trace of a recent stimulus and the neural representation of a new stimulus, one hypothesis is that this differential sensitivity between increment and decrement is caused by the downward decay of pitch’s memory trace. Under the same assumption, the present study found bidirectional—as opposed to the predicted unidirectional—decay of memory traces for pitch in speech sounds by measuring listeners' sensitivity to pitch change over varying time intervals with an AX discrimination task. Three properties in the AX task were randomly sampled from preset ranges: (1) f0 of the A token (163:320 Hz), (2) difference between the f0s of A and X (-30:30Hz), and (3) the inter-stimulus interval (ISI; 0:3 s). We found when the stimuli were in the lower portion of the speaker’s pitch range, listeners were less sensitive to pitch increments at larger ISIs. Meanwhile, when the stimuli were in the higher pitch range, listeners were less sensitive to pitch decrements at larger ISIs. These results suggest memory traces for pitch in speech sounds decay toward a center pitch.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".