An Auditory-Perceptual and Pupillometric Study of Vocal Strain and Listening Effort in Adductor Spasmodic Dysphonia
Bibliographic record
Abstract
This study evaluated ratings of vocal strain and perceived listening effort by normal hearing participants while listening to speech samples produced by talkers with adductor spasmodic dysphonia (AdSD). In addition, objective listening effort was measured through concurrent pupillometry to determine whether listening to disordered voices changed arousal as a result of emotional state or cognitive load. Recordings of the second sentence of the “Rainbow Passage” produced by talkers with varying degrees of AdSD served as speech stimuli. Twenty naïve young adult listeners perceptually evaluated these stimuli on the dimensions of vocal strain and listening effort using two separate visual analogue scales. While making the auditory-perceptual judgments, listeners’ pupil characteristics were objectively measured in synchrony with the presentation of each voice stimulus. Data analyses revealed moderate-to-high inter- and intra-rater reliability. A significant positive correlation was found between the ratings of vocal strain and listening effort. In addition, listeners displayed greater peak pupil dilation (PPD) when listening to more strained and effortful voice samples. Findings from this study suggest that when combined with an auditory-perceptual task, non-volitional physiologic changes in pupil response may serve as an indicator of listening and cognitive effort or arousal.
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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 | 0.003 |
| 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 | 0.000 |
| 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".