Voice quality of children with cochlear implants acquired at early and later ages
Bibliographic record
Abstract
The speech gains of children with cochlear implants (CIs) are well documented, but the literature on voice quality is sparse. It has reported atypical measures/ratings of voice pitch, pleasantness, timing, and acoustic features [Higgins et al. (2003); Perrin et al. (1998)]. Is voice quality now improving in children implanted very early? This pilot study compared the voice quality of (a) children with early acquired CIs and children with normal hearing and (b) the voice quality of children implanted later and earlier in life. Children aged 6 to 10 years, with early acquired CIs, and participants with normal hearing, age-matched to them, audio recorded sentences, vowels, and conversation. PERCI pressure measures were also performed. PERCI Differential and Oral Pressure values and Computerized Speech Lab (CSL) and Visipitch measures of voice-onset time and fundamental frequency were analyzed comparing the values from the hearing and the early implanted children and values gleaned from the study of Higgins et al. of children with later-acquired implants. CSL and Visipitch measures of intonation contour, intensity, and jitter were analyzed to compare the hearing and the early implanted participants. Ratings on the Wilson Voice Scale were correlated with measures of jitter, fundamental frequency, and intonation contour.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".