The Impact of Social–Cognitive Stress on Speech Variability, Determinism, and Stability in Adults Who Do and Do Not Stutter
Bibliographic record
Abstract
Purpose: This study examined the impact of social-cognitive stress on sentence-level speech variability, determinism, and stability in adults who stutter (AWS) and adults who do not stutter (AWNS). We demonstrated that complementing the spatiotemporal index (STI) with recurrence quantification analysis (RQA) provides a novel approach to both assessing and interpreting speech variability in stuttering. Method: Twenty AWS and 21 AWNS repeated sentences in audience and nonaudience conditions while their lip movements were tracked. Across-sentence variability was assessed via the STI; within-sentence determinism and stability were assessed via RQA. Results: Compared with the AWNS, the AWS produced speech that was more variable across sentences and more deterministic and stable within sentences. Audience presence contributed to greater within-sentence determinism and stability in the AWS. A subset of AWS who were more susceptible to experiencing anxiety exhibited reduced across-sentence variability in the audience condition compared with the nonaudience condition. Conclusions: This study extends the assessment of speech variability in AWS and AWNS into the social-cognitive domain and demonstrates that the characterization of speech within sentences using RQA is complementary to the across-sentence STI measure. AWS seem to adopt a more restrictive, less flexible speaking approach in response to social-cognitive stress, which is presumably a strategy for maintaining observably fluent speech.
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".