Labiodentalization of bilabial stops in spontaneous english smiled speech
Bibliographic record
Abstract
The co-occurrence of facial expressions and speech production presents a conflict of opposing muscular activation. Existing English research indicates a pattern of bilabial stops being resolved as labiodentals during smiled speech. Electromyographic data suggests that suppression is imposed on one muscle force to resolve the smiling-lip closure conflict [Liu et al., in ISSP Proceeding (2020), pp. 130–133]. These results have limited generalizability as data was collected from one speaker performing reading tasks under laboratory context. The present study continues the investigation of bilabial productions by investigating bilabial phonemes in spontaneous smiled speech. Natural speech samples from 16 native English speakers were extracted from YouTube interviews and vlogs. Bilabial phonemes in neutral and smiling conditions were analyzed for labiodentalization using facial imaging software. The intensity of Facial Action Units (FAU) “lip corner puller” and “lip tightener” during labial token productions were examined. Results show that labiodentalized variants of bilabial tokens also occurred during natural smiled speech. FAU intensity measurements indicate lower “lip corner puller” intensity during bilabial closures than labiodental ones when smiling. This suggests that smile suppression was observed when lip closure was prioritized, validating earlier laboratory conclusions that selective muscular suppression is utilized in the resolution of conflict between articulators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".