The effect of divided attention on phonetic imitation.
Bibliographic record
Abstract
Research suggests that phonetic imitation is an automatic and subconscious process, but it is clearly a behavior that is variable across participants and conditions. The purpose of this experiment is to explore how a participant’s level of attention to the speech signal moderates their degree of imitation. To this end, six conditions were prepared using a blocked exposure design: no redirection of attention (participants were instructed to simply listen to the model talker producing words), attention redirected through a math task, attention redirected through a picture-drawing task, attention focused through a word-memorization task, attention focused through a talker-description task, and attention focused through an explicit imitation task. A seventh condition using an immediate shadowing paradigm to compare to the blocked exposure design was run as well. Seventy native speakers of English (ten per condition) were recruited as participants. In all conditions participants’ baseline productions of the stimuli wordlist were recorded prior to exposure to the model talker (a female speaker of North American English). Recordings are currently being analyzed for imitation using various acoustic parameters including whole word duration, vowel spectra, and f0.
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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 | 0.014 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".