Real-time magnetic resonance imaging of velopharyngeal port posture during long pauses in naturalistic speech
Bibliographic record
Abstract
Velum’s behavior as a postural substrate in naturalistic speech is not well understood and is largely based on studies of inter-utterance velopharyngeal port posture (VPP). While existing literature [e.g., Gick et al., 2004 Phonetica, 61(4); Ramanarayanan, 2013 JASA, 134(1)] describes posture variations based on rest positions, ready positions, and inter-speech pauses, a less explored aspect is the behavior of the velum during extended pauses in naturalistic speech. Addressing this gap, the present study analyzes velum posture during naturalistic speech to characterize VPP during prolonged pauses. This study draws from a corpus of real-time magnetic resonance imaging (rtMRI) videos of L1 English speakers including those engaging in unstructured speech tasks. Results based on sequences corresponding to long pauses in naturalistic speech will be reported, outlining VPP characteristics, and quantifying findings in terms of time spent in and shifts between velum positions. Implications for motor control differences in naturalistic and elicited speech data will be discussed.
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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) | 0.001 | 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".