Auditory Feedback Control of Vocal Pitch during Sustained Vocalization: A Cross-Sectional Study of Adult Aging
Bibliographic record
Abstract
BACKGROUND: Auditory feedback has been demonstrated to play an important role in the control of voice fundamental frequency (F(0)), but the mechanisms underlying the processing of auditory feedback remain poorly understood. It has been well documented that young adults can use auditory feedback to stabilize their voice F(0) by making compensatory responses to perturbations they hear in their vocal pitch feedback. However, little is known about the effects of aging on the processing of audio-vocal feedback during vocalization. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we recruited adults who were between 19 and 75 years of age and divided them into five age groups. Using a pitch-shift paradigm, the pitch of their vocal feedback was unexpectedly shifted ±50 or ±100 cents during sustained vocalization of the vowel sound/u/. Compensatory vocal F(0) response magnitudes and latencies to pitch feedback perturbations were examined. A significant effect of age was found such that response magnitudes increased with increasing age until maximal values were reached for adults 51-60 years of age and then decreased for adults 61-75 years of age. Adults 51-60 years of age were also more sensitive to the direction and magnitude of the pitch feedback perturbations compared to younger adults. CONCLUSION: These findings demonstrate that the pitch-shift reflex systematically changes across the adult lifespan. Understanding aging-related changes to the role of auditory feedback is critically important for our theoretical understanding of speech production and the clinical applications of that knowledge.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".