Speech Intelligibility of Young School-Aged Children in the Presence of Real-Life Classroom Noise
Bibliographic record
Abstract
We examined the ability of 40 young children (aged five to eight) to understand speech (monosyllables, spondees, trochees, and trisyllables) when listening in a background of real-life classroom noise. All children had some difficulty understanding speech when the noise was at levels found in many classrooms (i.e., 65 dBA). However, at an intermediate (-6 dB SNR) level, kindergarten and grade 1 children had much more difficulty than did older children. All children performed well in quiet, with results being comparable to or slightly better than those reported in previous studies, suggesting that the task was age appropriate and well understood. These results suggest that the youngest children in the school system, whose classrooms also tend to be among he noisiest, are the most susceptible to the effects of noise. Evaluamos la capacidad de 40 niños (edades de cinco a ocho) para entender el lenguaje (monosilábicos, espondaicos, trocaicos y trisilábicos) al escucharlo en medio de un auténtico ruido de fondo de aula de clase. Todos los niños tuvieron alguna dificultad para entender el lenguaje cuando el ruido estuvo a los niveles hallados en muchas aulas de clase (p.e., 65 dBA). Sin embargo, a un nivel intermedio (-6 dBA), los niños de jardín de infantes y de primer grado tuvieron más dificultad que los niños mayores. Todos los niños funcionaron bien en silencio, con resultados comparables o hasta ligeramente superiores a los reportados en estudios previos, sugiriendo que la tarea era bien entendida y apropiada para la edad. Estos resultados sugieren que los niños más jóvenes dentro del sistema escolar, cuyas aulas de clase suelen ser las más ruidosas, son los más susceptibles a los efectos del ruido.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".