MétaCan
Menu
Retour à la cohorte
Enregistrement W1272428283 · doi:10.1097/aud.0000000000000207

The Effect of Residual Acoustic Hearing and Adaptation to Uncertainty on Speech Perception in Cochlear Implant Users

2015· article· en· W1272428283 sur OpenAlexaff
Bob McMurray, Ashley Farris‐Trimble, Michael Seedorff, Hannah Rigler

Notice bibliographique

RevueEar and Hearing · 2015
Typearticle
Langueen
DomaineNeuroscience
ThématiqueHearing Loss and Rehabilitation
Établissements canadiensSimon Fraser University
Organismes subventionnairesNational Institute on Deafness and Other Communication Disorders
Mots-clésVoiceCochlear implantPerceptCategorizationAudiologyPerceptionSpeech recognitionSpeech perceptionPsychologyComputer sciencePhoneticsLinguisticsMedicineArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

In Brief Objectives: While outcomes with cochlear implants (CIs) are generally good, performance can be fragile. The authors examined two factors that are crucial for good CI performance. First, while there is a clear benefit for adding residual acoustic hearing to CI stimulation (typically in low frequencies), it is unclear whether this contributes directly to phonetic categorization. Thus, the authors examined perception of voicing (which uses low-frequency acoustic cues) and fricative place of articulation (s/∫, which does not) in CI users with and without residual acoustic hearing. Second, in speech categorization experiments, CI users typically show shallower identification functions. These are typically interpreted as deriving from noisy encoding of the signal. However, psycholinguistic work suggests shallow slopes may also be a useful way to adapt to uncertainty. The authors thus employed an eye-tracking paradigm to examine this in CI users. Design: Participants were 30 CI users (with a variety of configurations) and 22 age-matched normal hearing (NH) controls. Participants heard tokens from six b/p and six s/∫ continua (eight steps) spanning real words (e.g., beach/peach, sip/ship). Participants selected the picture corresponding to the word they heard from a screen containing four items (a b-, p-, s- and ∫-initial item). Eye movements to each object were monitored as a measure of how strongly they were considering each interpretation in the moments leading up to their final percept. Results: Mouse-click results (analogous to phoneme identification) for voicing showed a shallower slope for CI users than NH listeners, but no differences between CI users with and without residual acoustic hearing. For fricatives, CI users also showed a shallower slope, but unexpectedly, acoustic + electric listeners showed an even shallower slope. Eye movements showed a gradient response to fine-grained acoustic differences for all listeners. Even considering only trials in which a participant clicked “b” (for example), and accounting for variation in the category boundary, participants made more looks to the competitor (“p”) as the voice onset time neared the boundary. CI users showed a similar pattern, but looked to the competitor more than NH listeners, and this was not different at different continuum steps. Conclusion: Residual acoustic hearing did not improve voicing categorization suggesting it may not help identify these phonetic cues. The fact that acoustic + electric users showed poorer performance on fricatives was unexpected as they usually show a benefit in standardized perception measures, and as sibilants contain little energy in the low-frequency (acoustic) range. The authors hypothesize that these listeners may overweight acoustic input, and have problems when this is not available (in fricatives). Thus, the benefit (or cost) of acoustic hearing for phonetic categorization may be complex. Eye movements suggest that in both CI and NH listeners, phoneme categorization is not a process of mapping continuous cues to discrete categories. Rather listeners preserve gradiency as a way to deal with uncertainty. CI listeners appear to adapt to their implant (in part) by amplifying competitor activation to preserve their flexibility in the face of potential misperceptions. We examined speech categorization in cochlear implant (CI) users and normal-hearing (NH) listeners using both phoneme categorization and eye-tracking. CI users showed shallower categorization slopes for voicing and fricative continua. While residual acoustic hearing did not affect voicing slopes, it led to even shallower functions for fricatives, despite the fact that fricatives do not contain information in the frequencies they receive acoustically. Eye-movements showed that both groups of listeners show a highly gradient response to fine-grained phonetic detail. Moreover, CI users exhibited heightened activation for competing words. This could be useful for preserving flexibility in the face of potential misperceptions.

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)0,001
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,912
Score d'incertitude au seuil0,198

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
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 Opus0,056
Tête enseignante GPT0,313
Écart entre enseignants0,257 · 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

Citations31
Publié2015
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueEar and HearingMême sujetHearing Loss and RehabilitationTravaux en français237 207