Intra-speaker and inter-speaker variability in speech sound pressure level across repeated readings
Bibliographic record
Abstract
The intra- and inter-speaker variability of speech sound pressure level (SPL) has been investigated under repeatability conditions in this work. In a semi-anechoic chamber, speech from 17 individuals was recorded with a sound level meter, a headworn microphone, and a vocal monitoring device. The subjects were asked to read twice and in sequence two phonetically balanced passages. The speech variability has been investigated for mean, equivalent, and mode SPL from each reading and device. The intra-speaker variability has been evaluated by means of the average among individual standard deviations in the four readings and it reached the maximum of 2 dB for mode SPL. For the inter-speaker variability, the experimental standard deviation of individual averaged SPL parameters among the four repeated measures has been calculated, obtaining the highest value of 5.3 dB for mode SPL. Changes in SPL variability have been evaluated with different logging intervals for each device. The influence of speech material has been investigated by the Wilcoxon test on paired lists of descriptive statistics for SPL distribution and equivalent SPL in the repeated readings. The data reported in this study may be considered as a preliminary reference for the investigation of changes in speech SPL over subjects.
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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 | 0.003 | 0.008 |
| 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 | 0.001 |
| 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".