Evaluation of Nonlinear Frequency Compression for School-Age Children with Moderate to Moderately Severe Hearing Loss
Bibliographic record
Abstract
BACKGROUND: Previous research has indicated that children with moderate hearing loss experience difficulty with recognition of high-frequency speech sounds, such as fricatives and affricates. Conventional behind-the-ear (BTE) amplification typically does not provide ample output in the high frequencies (4000 Hz and beyond) to ensure optimal audibility for these sounds. PURPOSE: To evaluate nonlinear frequency compression (NLFC) as a means to improve speech recognition for children with moderate to moderately severe hearing loss. RESEARCH DESIGN: Within subject, crossover design with repeated measures across test conditions. STUDY SAMPLE: Fifteen children, aged 5-13 yr, with moderate to moderately severe high-frequency sensorineural hearing loss were fitted with Phonak Nios, microsized, BTE hearing aids. These children were previous users of digital hearing aids and communicated via spoken language. Their speech and language abilities were age-appropriate. DATA COLLECTION AND ANALYSIS: Aided thresholds and speech recognition in quiet and in noise were assessed after 6 wk of use with NLFC and 6 wk of use without NLFC. Participants were randomly assigned to counter-balanced groups so that eight participants began the first 6 wk trial with NLFC enabled and the other seven participants started with NLFC disabled. Then, the provision of NLFC was switched for the second 6 wk trial. Speech recognition in quiet was assessed via word recognition assessments with the University of Western Ontario (UWO) Plural Test and recognition of vowel-consonant-vowel nonsense syllables with the Phonak Logatome test. Speech recognition in noise was assessed by evaluating the signal-to-noise ratio in dB for 50% correct performance on the Bamford-Kowal-Bench Speech-in-Noise (BKB-SIN) test, an adaptive test of speech perception in a multitalker babble background. RESULTS: Aided thresholds for high-frequency stimuli were significantly better when NLFC was enabled, and use of NLFC resulted in significantly better speech recognition in quiet for the UWO Plural Test and for the phonemes /d/ and /s/ on the Phonak Logatome test. There was not a statistically significant difference in performance on the BKB-SIN test between the NLFC enabled and disabled conditions. CONCLUSIONS: These results indicate that NLFC improves audibility for and recognition of high-frequency speech sounds for children with moderate to moderately severe hearing loss in quiet listening situations.
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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 | 0.002 |
| 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 | 0.001 |
| 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".