Acoustic Analysis of the Voice in Pediatric Cochlear Implant Recipients: A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: To characterize inherent acoustic abnormalities of the deaf pediatric voice and the effect of artificially restoring auditory feedback with cochlear implantation. DESIGN: Inception cohort. SETTING: Academic referral center. PATIENTS: Twenty-one children with severe to profound hearing loss (15 prelingually deaf, 6 postlingually deaf) accepted into the cochlear implant program were followed for up to 6 months. Patients unable to perform the vocal exercises were excluded. INTERVENTIONS: Objective voice analysis was performed using the Computerized Speech Laboratory (Kay Elemetrics) prior to cochlear implantation, at the time of implant activation and at 2 and 6 months postactivation. Assessments were based on sustained phonations and dynamic ranges. MAIN OUTCOME MEASURE: Fundamental frequency, long-term control of fundamental frequency (vF0) and long-term control of amplitude (vAM) were derived from sustained phonations. The dynamic frequency range was derived from scale exercises. Formant frequencies (F1, F2, F3) were determined using linear predictive coding. RESULTS: Fundamental frequency was not altered by implant activation or experience (P = 0.342). With profoundly deaf subject, the most prevalent acoustic abnormality was a poor long-term control of frequency (vF0, 2.81%) and long-term control of amplitude (vAm, 23.58%). Implant activation and experience had no effect on the long-term control of frequency (P = 0.106) but normalized the long-term control of amplitude (P = 0.007). The mean frequency range increased from 311.9 Hz preimplantation to 483.5 Hz postimplantation (P = 0.08). The F1/F2 ratio remained stable (P = 0.476). CONCLUSION: In children, severe to profound deafness results in poor long-term control of frequency and amplitude. Cochlear implantation restores control of amplitude only and implies the need for additional rehabilitative strategies for restoration of control of frequency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".