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Record W1973050006 · doi:10.1097/aud.0b013e3181daae5a

Children With Cochlear Implants Recognize Their Mother's Voice

2010· article· en· W1973050006 on OpenAlexafffund
Tara Vongpaisal, Sandra E. Trehub, E. Glenn Schellenberg, Pascal van Lieshout, Blake C. Papsin

Bibliographic record

VenueEar and Hearing · 2010
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUtterancePsychologyAudiologyProsodyCochlear implantStimulus (psychology)Context (archaeology)Task (project management)GirlTwo-alternative forced choiceDevelopmental psychologyAuditory feedbackSpeech recognitionCognitive psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

In Brief Objectives: The available research indicates that cochlear implant (CI) users have difficulty in differentiating talkers, especially those of the same gender. The goal of this study was to determine whether child CI users could differentiate talkers under favorable stimulus and task conditions. We predicted that the use of a highly familiar voice, full sentences, and a game-like task with feedback would lead to higher performance levels than those achieved in previous studies of talker identification in CI users. Design: In experiment 1, 21 CI users aged 4.8 to 14.3 yrs and 16 normal-hearing (NH) 5-yr-old children were required to differentiate their mother's scripted utterances from those of an unfamiliar man, woman, and girl in a four-alternative forced-choice task with feedback. In one condition, the utterances incorporated natural prosodic variations. In another condition, nonmaternal talkers imitated the prosody of each maternal utterance. In experiment 2, 19 of the child CI users and 11 of the NH children from experiment 1 returned on a subsequent occasion to participate in a task that required them to differentiate their mother's utterances from those of unfamiliar women in a two-alternative forced-choice task with feedback. Again, one condition had natural prosodic variations and another had maternal imitations. Results: Child CI users in experiment 1 succeeded in differentiating their mother's utterances from those of a man, woman, and girl. Their performance was poorer than the performance of younger NH children, which was at ceiling. Child CI users' performance was better in the context of natural prosodic variations than in the context of imitations of maternal prosody. Child CI users in experiment 2 differentiated their mother's utterances from that of other women, and they also performed better on naturally varying samples than on imitations. Conclusions: We attribute child CI users' success on talker differentiation, even on same-gender differentiation, to their use of two types of temporal cues: variations in consonant and vowel articulation and variations in speaking rate. Moreover, we contend that child CI users' differentiation of speakers was facilitated by long-term familiarity with their mother's voice. We assessed child implant users' ability to differentiate their mother's voice from the voices of unfamiliar speakers. In Experiment 1 they succeeded in differentiating their other's scripted utterances from those of a man, woman, and girl although their performance was poorer than that of younger children with normal hearing. Child implant users performed better for natural variations in speaking style than for imitations of the maternal style. In Experiment 2 child implant users differentiated their mother's utterances from those of other women, and they performed better on naturally varying samples than on imitations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.256
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2010
Admission routes2
Has abstractyes

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