Tongue Adjustments in the Chest-Head Register Transition of Operatic Singers
Bibliographic record
Abstract
The change in register from head to chest voice has been widely associated with laryngeal adjustments, including greater vocal fold adduction [Thalén & Sundberg (2009) LPV 26], longer glottal closed phase [Henrich, D. N. (2006) LPV 31], and vocal fold thickening [Herbst, Ternström, & Švec (2009) JASA 125]. Comparatively little research has looked at supralaryngeal adjustments across singing registers. Notably, Echternach and colleagues conducted a series of real-time MRI studies investigating the shape of the supraglottal vocal tract between registers. They found that the tongue dorsum was more elevated and farther back in falsetto than in modal voicing for operatic singers [Echternach et al. (2011a) J Voice 25]. A further study of classical singers and yodellers found the tongue dorsum was more elevated for higher pitches [Echternach et al. (2011b) LPV 31]. These studies showed significant variation across individuals and different vowels [Echternach et al. (2014) J Voice 28]. All of these previous studies, however, measured the tongue at only two points: tongue dorsum/body height and pharynx width. The present study aims to provide a more comprehensive investigation into the specific tongue adjustments made during register shifts. In particular, we will report on ultrasound imaging measurements of advancement and retraction of the tongue root and overall change in tongue contour. These measurements will be reported for trained opera singers producing transitions between chest and head register, across six vowels. Preliminary results indicate that singers raise the tongue body while advancing the tongue root across the chest-head transition. These findings contribute a more thorough understanding of the significance of tongue adjustments in register transitions.
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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 | 0.001 | 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) | 0.002 | 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".