Influence of Voice Focus Adjustments on Oral-Nasal Balance in Speech and Song
Bibliographic record
Abstract
OBJECTIVES: This study investigated the effect of training backward and forward voice focus adjustments on oral-nasal balance in speech and singing in typical speakers. METHODS: Twenty participants (10M/10F) aged 24.25 (SD 3.73) years read phonetically balanced, nasal and oral speech stimuli, and sang a song in both forward and backward voice focus conditions. A Nasometer 6450 was used to obtain nasalance scores in the different conditions. RESULTS: Results indicated that forward voice focus resulted in more nasality (p < 0.01) for the oral stimulus and song. Backward voice focus caused a decrease in nasality (p < 0.01) for the nasal stimulus, the phonetically balanced paragraph, and the song. During production of the song, males were more nasal in the forward voice focus condition than females (p = 0.01). CONCLUSIONS: Voice focus can influence oral-nasal balance in normal speakers. More research is needed to investigate whether voice focus adjustments could be helpful to speakers with oral-nasal balance disorders.
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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 | 0.001 |
| 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) | 0.003 | 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".