Articulatory peripherality modulates relative attention to the mouth during visual vowel discrimination
Bibliographic record
Abstract
Masapollo, Polka, and Ménard (2016) have recently reported that adults from different language backgrounds show robust directional asymmetries in unimodal visual-only vowel discrimination: a change in mouth-shape from one associated with a relatively less peripheral vowel to one associated with a relatively more peripheral vowel (in F1-F2 articulatory/acoustic vowel space) results in significantly better performance than a change in the reverse direction. In the present study, we used eye-tracking methodology to examine the gaze behavior of English-speaking subjects while they performed Masapollo et al.'s visual vowel discrimination task. We successfully replicated this directional effect using Masapollo et al.'s visual stimulus materials, and found that subjects deployed selective attention to the oral region compared to the ocular region of the model speaker's face. In addition, gaze fixations to the mouth were found to increase while subjects viewed the more peripheral vocalic articulations compared to the less peripheral articulations, perhaps due to their larger, more extreme oral-facial kinematic patterns. This bias in subjects’ pattern of gaze behavior may contribute to asymmetries in visual vowel perception.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".