Evidence map›Paper›PMID 32552327›Full record

ArticleJournal of speech, language, and hearing research : JSLHR2020

Effects of Age and Cochlear Implantation on Spectrally Cued Speech Categorization.

Mishaela DiNino, Julie G Arenberg, Anne L R Duchen, Matthew B Winn

Abstract read
In one paragraph

Article in Journal of speech, language, and hearing research : JSLHR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mishaela DiNinoDepartment of Psychology, Carnegie Mellon University, Pittsburgh, PA.
Julie G ArenbergMassachusetts Eye and Ear, Harvard Medical School Department of Otolaryngology, Boston.
Anne L R DuchenSeattle Children's Hospital, WA.
Matthew B WinnDepartment of Speech-Language-Hearing Sciences, University of Minnesota, Minneapolis.

Funding

Auditory Neuroscience Traning ProgramT32DC005361 · NIDCD · UNIVERSITY OF WASHINGTON · PI Adrian KC Lee, DAVID J PERKEL · 2002 to 2026
$8.8M
Perceptual implications of cochlear implant electrode-neuron interfacesR01DC012142 · NIDCD · UNIVERSITY OF WASHINGTON · PI JULIE G Arenberg · 2012 to 2026
$6.5M
Listening effort in cochlear implant usersR01DC017114 · NIDCD · UNIVERSITY OF MINNESOTA · PI Matthew Brandon Winn · 2018 to 2026
$3.4M
Measuring listening effort and spectral resolution in cochlear implant patientsR03DC014309 · NIDCD · UNIVERSITY OF WASHINGTON · PI WINN, MATTHEW BRANDON · 2016 to 2018
$455k
NIDCD NIH HHS R01 DC012142NIDCD NIH HHS R01 DC017114NIDCD NIH HHS R03 DC014309NIDCD NIH HHS T32 DC005361
6 · The paper itself

Abstract

Purpose Weighting of acoustic cues for perceiving place-of-articulation speech contrasts was measured to determine the separate and interactive effects of age and use of cochlear implants (CIs). It has been found that adults with normal hearing (NH) show reliance on fine-grained spectral information (e.g., formants), whereas adults with CIs show reliance on broad spectral shape (e.g., spectral tilt). In question was whether children with NH and CIs would demonstrate the same patterns as adults, or show differences based on ongoing maturation of hearing and phonetic skills. Method Children and adults with NH and with CIs categorized a /b/-/d/ speech contrast based on two orthogonal spectral cues. Among CI users, phonetic cue weights were compared to vowel identification scores and Spectral-Temporally Modulated Ripple Test thresholds. Results NH children and adults both relied relatively more on the fine-grained formant cue and less on the broad spectral tilt cue compared to participants with CIs. However, early-implanted children with CIs better utilized the formant cue compared to adult CI users. Formant cue weights correlated with CI participants' vowel recognition and in children, also related to Spectral-Temporally Modulated Ripple Test thresholds. Adults and child CI users with very poor phonetic perception showed additive use of the two cues, whereas those with better and/or more mature cue usage showed a prioritized trading relationship, akin to NH listeners. Conclusions Age group and hearing modality can influence phonetic cue-weighting patterns. Results suggest that simple nonlexical categorization tests correlate with more general speech recognition skills of children and adults with CIs.

Indexed as

Cochlear ImplantationCochlear ImplantsSpeech PerceptionAdultChildCuesHumansSpeech

Identifiers

PMID32552327
PMCPMC7838840

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.