Extending the Hearing-Aid Speech Perception Index (HASPI): Keywords, sentences, and context
Bibliographic record
Abstract
The Hearing-Aid Speech Perception Index version 2 (HASPI v2) is a speech intelligibility metric derived by fitting subject responses scored as the proportion of complete sentences correct. This paper presents an extension of HASPI v2, denoted by HASPI w2, which predicts proportion keywords correct for the same datasets used to derive HASPI v2. The results show that the accuracy of HASPI w2 is nearly identical to that of HASPI v2. The values produced by HASPI w2 and HASPI v2 also allow the comparison of proportion words correct and sentences correct for the same stimuli. Using simulation values for speech in additive noise, a model of context effects for words combined into sentences is developed and accounts for the loss of intelligibility inherent in the impaired auditory periphery. In addition, HASPI w2 and HASPI v2 have a small bias term at poor signal-to-noise ratios; the model for context effects shows that the residual bias is reduced in converting from proportion keywords to sentences correct but is greatly magnified when considering the reverse transformation.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".