Laryngeal-acoustic relations in smiled speech
Bibliographic record
Abstract
Smiling is a social signal that can be both seen and heard. Smiling can increase speech amplitude and raise F0 and formants. However, experimental research on the role of larynx height in smiled speech is limited. 21 English speakers (6 M) repeated words in a carrier phrase with a neutral face or while smiling. The participants were recorded with audio, video and laryngeal ultrasound. F0, F1 and F2 were extracted for the duration of target vowels /i/, /u/ and /a/. Ultrasound images of laryngeal position were measured using Optical Flow. The laryngeal and acoustic data were analyzed in R with linear mixed models with smiling condition, timepoint-in-vowel, and gender as fixed effects. There was a significant effect of timepoint-in-vowel for larynx height (raising towards the end) and a smile-timepoint interaction effect (the larynx raised more at the end for smiling condition). Acoustically, smiling led to significantly higher F0 across vowels, and significantly higher F1 and F2 for /a/ but not /i/ or /u/. F2 timepoints were significant for all three vowels (F2 trajectories differed) across smile conditions. Results indicate smiling has a consistent effect on larynx height and variable effect on specific speech sounds.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".