How Age, Linguistic Status, and the Nature of the Auditory Scene Alter the Manner in which Listening Comprehension is Achieved in Multi-talker Listening Situations
Notice bibliographique
Résumé
Conversations in noise challenge the perceptual and cognitive capabilities of older adults and those listening in their second language (L2), and might force them to alter the balance between the contributions of bottom-up versus top-down processes involved in spoken language comprehension. We investigated the extent to which individual differences in vocabulary and reading comprehension skills are related to individual differences in spoken language comprehension. In Experiments 1 and 2 younger and older L1s as well as young L2s listened to conversations in English played against a babble background and answered questions regarding their content. Individual hearing differences were compensated for by creating the same degree of difficulty in recognizing spoken words in babble. In Experiment, 1 two-talker conversations were played with or without either real or virtual spatial separation between the talkers and masker. The results showed that all listeners performed better when there appeared to be spatial separation. The contribution of vocabulary to dialogue comprehension was larger when spatial location was virtual rather than real, whereas the contribution of reading comprehension differed as a function of age and language proficiency. In Experiment 2, three-talker conversations, with or without spatial separation, were played in either quiet or against moderate or high babble. The contribution of individual differences in vocabulary and reading comprehension skills differed among the groups, and the babble level. In both experiments compensating for differences in spoken word recognition, minimized the differences in conversation comprehension among the groups. In addition, the manner in which spoken language comprehension is achieved is modulated by the auditory scene, and the listeners' age and linguistic status.Experiment 3 investigated how the perceived compactness of sound sources affects spoken language recognition. Younger L1s, older L1s and young L2s were asked to repeat meaningless sentences played in noise, babble or speech, either with or without contrast of diffuseness between target and masker. Results showed a release of masking due to contrast, which was greater when the masker was speech compared with noise. Individual differences in speech recognition were related to individual differences in vocabulary and reading comprehension in young L2s and older L1s only.
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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) | 0,000 | 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 | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».