Auditory Processing Disorder and Speech Perception Problems in Noise: Finding the Underlying Origin
Bibliographic record
Abstract
PURPOSE: A hallmark listening problem of individuals presenting with auditory processing disorder (APD) is their poor recognition of speech in noise. The underlying perceptual problem of the listening difficulties in unfavorable listening conditions is unknown. The objective of this article was to demonstrate theoretically how to determine whether the speech recognition problems are related to an auditory dysfunction, a language-based dysfunction, or a combination of both. METHOD: Tests such as the Speech Perception in Noise (SPIN) test allow the exploration of the auditory and language-based functions involved in speech perception in noise, which is not possible with most other speech-in-noise tests. Psychometric functions illustrating results from hypothetical groups of individuals with APD on the SPIN test are presented. This approach makes it possible to postulate about the origin of the speech perception problems in noise. CONCLUSION: APD is a complex and heterogeneous disorder for which the underlying deficit is currently unclear. Because of their design, SPIN-like tests can potentially be used to identify the nature of the deficits underlying problems with speech perception in noise for this population. A better understanding of the difficulties with speech perception in noise experienced by many listeners with APD should lead to more efficient intervention programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".