Acoustic and articulatory correlates of contrastive focus
Bibliographic record
Abstract
This paper aims at examining production of French speakers in marking focus-induced prominence at the articulatory and acoustic levels. The corpus consisted of CVC syllables, where C corresponds to one of the stops /p t k/ and V is one of the vowels /i a u/. Target words were embedded in carrier sentences elicited in two prosodic conditions: neutral (unfocused) and under contrastive focus. Four adult speakers (all native speakers of French) pronounced ten repetitions of each sequence. The audio signal and tongue shapes were recorded using a digital camera and a SONOSITE 180 ultrasound. Formant frequencies, rms values, duration, and tongue contours corresponding to each vowel were extracted. Analyses show that prosodic context has a significant effect on acoustic and articulatory data for all vowels, increasing F1 and F2 under contrastive focus, compared to the neutral context. However, this stable acoustic pattern is achieved by various articulatory strategies across subjects. For example, 2 subjects produced /u/ under focus with a lower tongue body than in the neutral context, whereas the remaining 2 subjects had a higher tongue body in focused syllables. Results are compared to previous studies on articulatory and acoustic correlates of prosodic structure in French and English.
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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 | 0.002 |
| 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) | 0.002 | 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".