Word Recognition for Temporally and Spectrally Distorted Materials
Notice bibliographique
Résumé
In Brief Objectives: The purpose of Experiment 1 was to measure word recognition in younger adults with normal hearing when speech or babble was temporally or spectrally distorted. In Experiment 2, older listeners with near-normal hearing and with hearing loss (for pure tones) were tested to evaluate their susceptibility to changes in speech level and distortion types. The results across groups and listening conditions were compared to assess the extent to which the effects of the distortions on word recognition resembled the effects of age-related differences in auditory processing or pure-tone hearing loss. Design: In Experiment 1, word recognition was measured in 16 younger adults with normal hearing using Northwestern University Auditory Test No. 6 words in quiet and the Words-in-Noise test distorted by temporal jittering, spectral smearing, or combined jittering and smearing. Another 16 younger adults were evaluated in four conditions using the Words-in-Noise test in combinations of unaltered or jittered speech and unaltered or jittered babble. In Experiment 2, word recognition in quiet and in babble was measured in 72 older adults with near-normal hearing and 72 older adults with hearing loss in four conditions: unaltered, jittered, smeared, and combined jittering and smearing. Results: For the listeners in Experiment 1, word recognition was poorer in the distorted conditions compared with the unaltered condition. The signal to noise ratio at 50% correct word recognition was 4.6 dB for the unaltered condition, 6.3 dB for the jittered, 6.8 dB for the smeared, 6.9 dB for the double-jitter, and 8.2 dB for the combined jitter-smear conditions. Jittering both the babble and speech signals did not significantly reduce performance compared with jittering only the speech. In Experiment 2, the older listeners with near-normal hearing and hearing loss performed best in the unaltered condition, followed by the jitter and smear conditions, with the poorest performance in the combined jitter-smear condition in both quiet and noise. Overall, listeners with near-normal hearing performed better than listeners with hearing loss by ~30% in quiet and ~6 dB in noise. In the quiet distorted conditions, when the level of the speech was increased, performance improved for the hearing loss group, but decreased for the older group with near-normal hearing. Recognition performance of younger listeners in the jitter-smear condition and the performance of older listeners with near-normal hearing in the unaltered conditions were similar. Likewise, the performance of older listeners with near-normal hearing in the jitter-smear condition and the performance of older listeners with hearing loss in the unaltered conditions were similar. Conclusions: The present experiments advance our understanding regarding how spectral or temporal distortions of the fine structure of speech affect word recognition in older listeners with and without clinically significant hearing loss. The Speech Intelligibility Index was able to predict group differences, but not the effects of distortion. Individual differences in performance were similar across all distortion conditions with both age and hearing loss being implicated. The speech materials needed to be both spectrally and temporally distorted to mimic the effects of age-related differences in auditory processing and hearing loss. The purpose of these experiments was to measure word recognition when speech was temporally or spectrally distorted, and to examine the ef-fects of speech levels and distortion types on older listeners with near-normal hearing or hearing loss. In quiet, with increased speech level in dis-tortion, performance improved for the hearing-loss group, but not for the near-normal-hearing group. There was a resemblance between the per-formance of younger listeners in distortion and that of older listeners with near-normal hearing in unaltered conditions, and between older listen-ers with near-normal hearing in distortion and older listeners with hearing loss in unaltered conditions.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».