Children With Cochlear Implants Recognize Their Mother's Voice
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".