Children's Perception of Speaker Identity from Spectrally Degraded Input
Notice bibliographique
Résumé
Speaker identification is a challenge for cochlear implant users because their prosthesis restricts access to the cues that underlie natural voice quality. The present thesis examined speaker recognition in the context of spectrally degraded sentences. The listeners of interest were child implant users who were prelingually deaf as well as hearing children and adults who listened to speech via vocoder simulations of implant processing. Study 1 focused on child implant users' identification of a highly salient speaker—the mother (identified as mother)—and unfamiliar speakers varying in age and gender (identified as man, woman, or girl). In a further experiment, children were required to differentiate their mother's voice from the voices of unfamiliar women. Young hearing children were tested on the same tasks and stimuli. Although child implant users performed more poorly than hearing children overall, they successfully differentiated their mother's voice from other voices. In fact, their performance surpassed expectations based on previous studies of child and adult implant users. Even when natural variations in speaking style were reduced, child implant users successfully identified the speakers. The findings imply that person-specific differences in articulatory style contributed to implanted children's successful performance. Study 2 used vocoder simulations of cochlear implant processing to vary the spectral content of sentences produced by the man, woman, and girl from Study 1. The ability of children (5-7 years and 10-12 years) and adults with normal hearing to identify the speakers was affected by the level of spectral degradation and by the gender of the speaker. Female voices were more difficult to identify than was the man's voice, especially for the younger children. In some respects, hearing individuals' identification of degraded voices was poorer than that of child implant users in Study 1. In a further experiment, hearing children and adults were required to provide verbatim repetitions of spectrally degraded sentences. Their performance on this task greatly exceeded their performance on speaker identification at comparable levels of spectral degradation. The present findings underline the importance of ecologically valid materials and methods when assessing speaker identification, especially in children. Moreover, they raise questions about the efficacy of vocoder models for the study of speaker identification in cochlear implant users.
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) | 0,000 | 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 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».