Speech-Evoked Envelope Following Responses in Children and Adults
Bibliographic record
Abstract
PURPOSE: Envelope following responses (EFRs) could be useful for objectively evaluating audibility of speech in children who are unable to participate in routine clinical tests. However, relative to adults, the characteristics of EFRs elicited by frequency-specific speech and their utility in predicting audibility in children are unknown. METHOD: EFRs were elicited by the first (F1) and second and higher formants (F2+) of male-spoken vowels /u/ and /i/ and by fricatives /ʃ/ and /s/ in the token /suʃi/ presented at 15, 35, 55, 65, and 75 dB SPL. The F1, F2+, and fricatives were low-, mid-, and high-frequency dominant, respectively. EFRs were recorded between the vertex and the nape from twenty-three 6- to 17-year-old children and 21 young adults with normal hearing. Sensation levels of stimuli were estimated based on behavioral thresholds. RESULTS: In children, amplitude decreased with age for /ʃ/-elicited EFRs but remained stable for low- and mid-frequency stimuli. As a group, EFR amplitude and phase coherence did not differ from that of adults. EFR sensitivity (proportion of audible stimuli detected) and specificity (proportion of inaudible stimuli not detected) did not vary between children and adults. Consistent with previous work, EFR sensitivity increased with stimulus frequency and level. The type of statistical indicator used for EFR detection did not influence accuracy in children. CONCLUSIONS: Adultlike EFRs in 6- to 17-year-old typically developing children suggest mature envelope encoding for low- and mid-frequency stimuli. EFR sensitivity and specificity in children, when considering a wide range of stimulus levels and audibility, are ~77% and ~92%, respectively. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21136171.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".