MétaCan
Menu
Retour à la cohorte
Enregistrement W4415781293 · doi:10.1097/aud.0000000000001754

Modeling the Relationship Between Listener Factors and Envelope Fidelity: A Pooled Analysis Spanning a Decade

2025· article· en· W4415781293 sur OpenAlexaff
Varsha H. Rallapalli, Jeff Crukley, Emily Lundberg, James M. Kates, Kathryn H. Arehart, Pamela E. Souza

Notice bibliographique

RevueEar and Hearing · 2025
Typearticle
Langueen
DomaineNeuroscience
ThématiqueHearing Loss and Rehabilitation
Établissements canadiensMcMaster UniversityUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésIntelligibility (philosophy)Hearing aidFidelitySpeech perceptionMetric (unit)Envelope (radar)Hearing lossHigh fidelitySpeech processing

Résumé

récupéré en direct d'OpenAlex

OBJECTIVES: There is a large variability in speech intelligibility with hearing aids. This variability remains despite the current clinical approaches that provide individualized frequency-specific adjustments to gain in hearing aids. Much of this variability documented in the literature may also be due to differences across studies in terms of outcome measures, test conditions, etc. The objective of this study was to model sources of individual variability in speech intelligibility with hearing aids, in a pooled analysis across four distinct studies that used common methodologies and outcome measures. DESIGN: Deidentified data from 80 unique listeners with bilateral mild to moderately severe sensorineural hearing loss and aged 49 to 92 years were pooled from four published studies. A hierarchical Beta-Binomial (generalized linear mixed-effects) model was implemented to estimate the probability of correct word recognition in the pooled data using a Bayesian framework. Across studies, word recognition was measured for low-context sentences, in multi-talker babble, for a range of signal to noise ratios. Signals were processed through a hearing aid simulator or a wearable device and were customized to the listener's audiogram. Individual studies involved systematic manipulations of wide dynamic range compression, frequency lowering, or microphone directionality. Individual working memory ability was measured using the reading span test. A well-established auditory metric was used to quantify cumulative envelope fidelity (cepstral correlation) from background noise and the hearing aid processing for each listener. RESULTS: The model showed a strong relationship between speech intelligibility and envelope fidelity, confirming previous research findings that higher envelope fidelity was associated with better speech intelligibility. Among the sources of individual variability, working memory had a significant effect on the relationship between speech intelligibility and envelope fidelity. Listeners with higher working memory had significantly better word recognition than those with lower working memory, especially when envelope fidelity was worse. In addition, listeners with lower working memory had better word recognition as envelope fidelity increased. Age and degree of hearing loss (four-frequency pure-tone average) did not have a significant effect on the relationship between speech intelligibility and envelope fidelity. CONCLUSIONS: The analysis of the pooled dataset identified sources of individual variability in aided speech intelligibility, while also overcoming limitations of smaller sample sizes in prior research. The model supported the hypothesis that speech intelligibility is affected by the cumulative envelope fidelity arising from a combination of background noise and hearing aid processing. The study findings indicate that individual variability in speech intelligibility with hearing aid processing is related to working memory after accounting for age and degree of hearing loss. The study highlights the need for individualized treatment of hearing loss beyond the pure tone audiogram. Auditory metrics such as the envelope fidelity metric used in the study may be useful tools in clinical decision-making.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,039
Score d'incertitude au seuil0,436

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,109
Tête enseignante GPT0,340
Écart entre enseignants0,231 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueEar and HearingMême sujetHearing Loss and RehabilitationTravaux en français237 207