Do Not Cut Off Your Tail: A Mega-Analysis of Responses to Auditory Perturbation Experiments
Bibliographic record
Abstract
PURPOSE: The practice of removing "following" responses from speech perturbation analyses is increasingly common, despite no clear evidence as to whether these responses represent a unique response type. This study aimed to determine if the distribution of responses to auditory perturbation paradigms represents a bimodal distribution, consisting of two distinct response types, or a unimodal distribution. METHOD: This mega-analysis pooled data from 22 previous studies to examine the distribution and magnitude of responses to auditory perturbations across four tasks: adaptive pitch, adaptive formant, reflexive pitch, and reflexive formant. Data included at least 150 unique participants for each task, with studies comprising younger adult, older adult, and Parkinson's disease populations. A Silverman's unimodality test followed by a smoothed bootstrap resampling technique was performed for each task to evaluate the number of modes in each distribution. Wilcoxon signed-ranks tests were also performed for each distribution to confirm significant compensation in response to the perturbation. RESULTS: > .05) for any group or task, indicating unimodal distributions. Our analyses also confirmed compensatory reflexive responses to pitch and formant perturbations across all groups, as well as adaptive responses to sustained formant perturbations. However, analyses of sustained pitch perturbations only revealed evidence of adaptation in studies with younger adults. CONCLUSION: The demonstration of a clear unimodal distribution across all tasks suggests that following responses do not represent a distinct response pattern, but rather the tail of a unimodal distribution. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24282676.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".