Assessing acoustic measures of the spontaneous phonetic imitation of vowels.
Bibliographic record
Abstract
It is well established that people imitate fine phonetic detail of another talker in shadowing tasks [Goldinger, Psych. Rev. 105, 251–279 (1998)] and in interactive conversation [Pardo, J. Acoust. Soc. Am. 119, 2382–2393 (2006)]. That is, the acoustic characteristics of a model talker’s production (MTP) are more similar to a participant’s shadowed production (PSP) than they are to that participant’s baseline production (PBP), typically elicited in a reading task. This presentation compares two methods of assessing the acoustic distance between the vowels in PSP and PBP monosyllabic words taken from two previous studies [Babel, thesis, University of California (2009); Kaiser & Munson, (unpublished)]. One of these measures is the F1/F2 Euclidean distance between PSP and PBP vowels. This measure does not take into account the direction of the difference. The other [adapted from Titze, Principles of Voice Production (1994)] compares the distance and direction of the F1 and F2 values in the PSP and PBP vowels relative to those of the MTP. The merits of each of these methods are assessed by comparing them to measures of listener judgments of the similarity of PSPs and PBPs to the MTPs in AXB perception tasks.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".