Changes in Voice Quality after a Pure Tone Stimulation (PTS) Program
Bibliographic record
Abstract
Background: Auditory feedback allows individuals to monitor their vocal characteristics and adjust to maintain optimal voice quality. One type of auditory stimulation for conversational voice training/therapy is pure tone stimulation. This technique presents binaural auditory stimuli consisting of pure tones separated by half-step intervals to modify the fundamental frequency of the speaking voice and expand the vocal range. Objectives: This study aimed to characterize detectable changes in voice production following the application of pure tone stimulation (PTS) among speakers with and without voice disorders. Methods: Data from thirty-nine participants (28 individuals with voice disorders and 11 individuals with normal voices) were analyzed for this study. All participants engaged in binaural PTS exercises. Participants recorded a sustained vowel /a/ before and after the PTS exercises. Multiple acoustic voice parameters were extracted from the sustained vowel samples (fundamental frequency, pitch strength, harmonics-to-noise ratio, and smoothed cepstral peak prominence). Additionally, a visual analogue scale (VAS) interpretation of narrowband (NB) spectrograms was conducted to assess voice quality. Results: Statistically significant increases in fundamental frequency were found after the PTS exercises, except for males in the normal voices group. Pitch strength increased after the PTS, regardless of gender. Participants also demonstrated an increase in the harmonics-to-noise ratio. VAS ratings of NB spectrograms indicated improvement in voice quality following the program. Conclusions: Voice changes after performing PTS suggest voice quality improvement, as measured by acoustic analysis of vowel production and qualitative assessment of NB spectrograms among participants with and without voice 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 | 0.002 |
| 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".