Evaluation of Wideband Frequency Responses and Nonlinear Frequency Compression for Children with Cookie-Bite Audiometric Configurations
Notice bibliographique
Résumé
BACKGROUND: Previous research has suggested that use of nonlinear frequency compression (NLFC) can improve audibility for high-frequency sounds and speech recognition of children with moderate to profound high-frequency hearing loss. Furthermore, previous studies have generally found no detriment associated with the use of NLFC. However, there have been no published studies examining the effect of NLFC on the performance of children with cookie-bite audiometric configurations. For this configuration of hearing loss, frequency-lowering processing will likely move high-frequency sounds to a lower frequency range at which a greater degree of hearing loss exists. PURPOSE: The purpose of this study was to evaluate and compare the effects of wideband amplification and NLFC on high-frequency audibility and speech recognition of children with cookie-bite audiometric configurations. RESEARCH DESIGN: This study consisted of a within-participant design with repeated measures across test conditions. STUDY SAMPLE: Seven children, ages 6-13 yr, with cookie-bite audiometric configurations and normal hearing or mild hearing loss at 6000 and 8000 Hz, were recruited. INTERVENTION: Participants were fitted with Phonak Nios S H2O III behind-the-ear hearing aids and Oticon Safari 300 behind-the-ear hearing aids. DATA COLLECTION: The participants were evaluated after three 4-to 6-wk intervals: (1) Phonak Nios S H2O III without NLFC, (2) Phonak Nios S H2O III with NLFC, and (3) Oticon Safari 300 with wideband frequency response extending to 8000 Hz. The order in which each technology was used was counterbalanced across participants. High-frequency audibility was evaluated by assessing aided thresholds (dB SPL) for warble tones and the high-frequency phonemes /sh/ and /s/. Speech recognition in quiet was measured with the University of Western Ontario (UWO) Plurals Test, the UWO Distinctive Features Difference (DFD) Test, and the Phoneme Perception Test vowel-consonant-vowel nonsense syllable test. Sentence recognition in noise was evaluated with the Bamford-Kowal-Bench Speech-In-Noise (BKB-SIN) Test. ANALYSIS: Repeated-measures analyses of variance were used to analyze the data collected in this study. The results across the three different conditions were compared. RESULTS: No difference in performance across conditions was observed for detection of high-frequency warble tones and the speech sounds /sh/ and /s/. No significant difference was seen across conditions for speech recognition in quiet when measured with the UWO Plurals Test, the UWO-DFD Test, and the Phoneme Perception Test vowel-consonant-vowel nonsense syllable test. Finally, there were also no differences across conditions on the BKB-SIN Test. CONCLUSIONS: These results suggest that NLFC does not degrade or improve audibility for and recognition of high-frequency speech sounds as well as sentence recognition in noise when compared with wideband amplification for children with cookie-bite audiometric configurations.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».