Delay detectability and speech rate as a function of delay duration in auditory feedback.
Bibliographic record
Abstract
The relationship between delayed auditory feedback and speech rate, speech error rate, and delay detectability was examined as a function of delay duration. Thirty adult participants read paragraphs while listening to delayed feedback at 10 logarithmically spaced delay durations between 0 and 180 ms. Significant main effects of delay duration was found for speech rate as well as number of disfluencies. In addition, there was a significant effect of delay duration on the detectability of the delay as well as on reaction times even for very short delays (i.e., 16 ms). For reasons that are currently unknown, delays at 45 ms were significantly more difficult to detect than delays of either 32 or 64 ms. This was evident for both reaction-time data as well as signal-detection data. There was a linear, downward trend in speech rate for delays of 32 ms and longer, with a small deviation at 45 ms. Disfluencies were infrequent but there were significant increases in stuttering-like disruptions at longer delays (i.e., 128–180 ms). [Work supported by SSHRC.]
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 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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".