Timing of smile suppression during the articulation of labials in smiled speech
Bibliographic record
Abstract
Past studies have shown that opposing forces on the lips can be reconciled by suppressing a smile during speech-related lip closure movements [Liu et al., 2020, ISSP]. However, the exact timing of this suppression on the smiling posture remains unknown. The purpose of this study was to determine the onset and duration of smile suppression during labial production in smiled speech. We collected video footage of participants reading sentences that contain labial sounds (/m, f, v, b, p, w/) under three facial posture conditions (neutral, smile, laugh), and extracted short video clips of the labial sound productions. We then analyzed the extent of lip spreading in each facial posture condition using OpenFace 2.0 [Baltrušaitis et al., 2018, IEEE]. Our preliminary results show that smile is suppressed in the smiling and laughing conditions, with attenuation beginning approximately 300ms prior to labial sound production, and continuing for about 600ms regardless of conditions. Further analysis will investigate the duration of suppression after the offset of labials and will be conducted on more participants.
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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 | 0.004 |
| 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 | 0.001 |
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".