Development of the speech test signal in Brazilian Portuguese for real-ear measurement
Bibliographic record
Abstract
OBJECTIVE: Recommended practice is to verify the gain and/or output of hearing aids with speech or speech-shaped signals. This study has the purpose of developing a speech test signal in Brazilian Portuguese that is electroacoustically similar to the international long-term average speech spectrum (ILTASS) for use in real ear verification systems. DESIGN: A Brazilian Portuguese speech passage was recorded using standardized equipment and procedures for one female talker and compared to ISTS. The passage consisted of simple, declarative sentences making a total of 148 words. STUDY SAMPLE: The recordings of a Brazilian Portuguese passage were filtered to the ILTASS and compared to the International Speech Test Signal (ISTS). Aided recordings were made at three test levels, for three audiograms for the Brazilian Portuguese passage and the ISTS. RESULTS: The unaided test signals were spectrally matched to within 0.5 dB. Aided evaluation revealed that the Brazilian Portuguese passage produced aided spectra that were within 1 dB on average, within about 2 dB per audiogram, and within about 3 dB per frequency for 95% of fittings. CONCLUSION: Results indicate that the Brazilian Portuguese passage developed in this study provides similar electroacoustic hearing-aid evaluations to those expected from the standard ISTS passage.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".