The Impact of Feedback Frequency on Performance in a Novel Speech Motor Learning Task
Bibliographic record
Abstract
Purpose: This study investigated whether whole nonword accuracy, phoneme accuracy, and acoustic duration measures were influenced by the amount of feedback speakers without impairment received during a novel speech motor learning task. Method: Thirty-two native English speakers completed a nonword production task across 3 time points: practice, short-term retention, and long-term retention. During practice, participants received knowledge of results feedback according to a randomly assigned schedule (100%, 50%, 20%, or 0%). Changes in nonword accuracy, phoneme accuracy, nonword duration, and initial-cluster duration were compared among feedback groups, sessions, and stimulus properties. Results: All participants improved phoneme and whole nonword accuracy at short-term and long-term retention time points. Participants also refined productions of nonwords, as indicated by a decrease in nonword duration across sessions. The 50% group exhibited the largest reduction in duration between practice and long-term retention for nonwords with native and nonnative clusters. Conclusions: All speakers, regardless of feedback schedule, learned new speech motor behaviors quickly with a high degree of accuracy and refined their speech motor skills for perceptually accurate productions. Acoustic measurements may capture more subtle, subperceptual changes that may occur during speech motor learning. Supplemental Materials: https://doi.org/10.23641/asha.5116324.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".