The Effect of Auditory Information on Patterns of Intrusions and Reductions
Bibliographic record
Abstract
PURPOSE: The study investigates whether auditory information affects the nature of intrusion and reduction errors in reiterated speech. These errors are hypothesized to arise as a consequence of autonomous mechanisms to stabilize movement coordination. The specific question addressed is whether this process is affected by auditory information so that it will influence the occurrence of intrusions and reductions. METHODS: Fifteen speakers produced word pairs with alternating onset consonants and identical rhymes repetitively at a normal and fast speaking rate, in masked and unmasked speech. Movement ranges of the tongue tip, tongue dorsum, and lower lip during onset consonants were retrieved from kinematic data collected with electromagnetic articulography. Reductions and intrusions were defined as statistical outliers from movement range distributions of target and nontarget articulators, respectively. RESULTS: Regardless of masking condition, the number of intrusions and reductions increased during the course of a trial, suggesting movement stabilization. However, compared with unmasked speech, speakers made fewer intrusions in masked speech. The number of reductions was not significantly affected. CONCLUSIONS: Masking of auditory information resulted in fewer intrusions, suggesting that speakers were able to pay closer attention to their articulatory movements. This highlights a possible stabilizing role for proprioceptive information in speech movement coordination.
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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 | 0.011 |
| 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 | 0.001 |
| 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".