Age-related differences in the sequential organization of speech sounds
Bibliographic record
Abstract
This study investigated the effects of age on listeners' tendency to group speech tokens into one or two auditory streams. Younger and older adults were presented with sequences of four vowel sounds, which were arranged according to the proximity of first-formant frequencies between adjacent vowels. In Experiment 1, participants were less accurate in identifying the order of the four vowels and more likely to report hearing two streams when the first-formant alternated between low and high frequency and the overall difference between adjacent vowels was large. This effect of first-formant continuity on temporal order judgments and probability of hearing two streams was higher in younger than in older adults. In Experiment 2, participants indicated whether there was rhythm irregularity in an otherwise isochronous sequence of four vowels. Young adults' thresholds were lower when successive first-formants ascended or descended monotonically (condition promoting integration) than when they alternated discontinuously (condition promoting streaming). This effect was not observed in older adults whose thresholds were comparable for both types of vowel sequences. These two experiments provide converging evidence for an age-related deficit in exploiting first-formant information between consecutive vowels, which appear to impede older adults' ability to sequentially group speech sounds over time.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".