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Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
Published on: March 24, 2023
Children's consonant inventories after extended cochlear implant use
1Indiana University, School of Medicine, Department of Otolaryngology-HNS, Indianapolis 46202-5119, USA. schin@iupui.edu
Journal of Speech, Language, and Hearing Research : JSLHR
|September 10, 2003
Summary
Children using cochlear implants develop unique consonant inventories, not just subsets of English sounds. Understanding these diverse phonological systems is crucial for effective speech habilitation.
Area of Science:
- Speech-Language Pathology
- Audiology
- Linguistics
Background:
- Cochlear implants (CIs) significantly impact speech sound development in children.
- Understanding the phonological systems of CI users is vital for habilitation.
- Previous research often assumes CI users' inventories are subsets of the ambient language.
Purpose of the Study:
- To qualitatively describe the consonant inventories of children with long-term CI use.
- To analyze sound correspondences between children's systems and English.
- To identify differences in inventories based on communication mode (oral vs. total communication).
Main Methods:
- Elicited productions of English words using a picture-naming task.
- Determined consonant inventories for 12 children with at least 5 years of CI use.
- Compared inventories of oral communication (OC) users and total communication (TC) users.
Main Results:
- Consonant inventories of CI users are unique sets, not mere subsets of English.
- Some inventories included non-English sound segments.
- OC users' inventories had more English segments (e.g., alveolar fricatives, velar stops/nasals).
- TC users' inventories showed a higher prevalence of non-English segments (e.g., uvular stops).
Conclusions:
- A comprehensive understanding of CI users' phonological systems requires detailed segment inventory analysis.
- Phonological system differences between OC and TC users were observed.
- Accurate habilitation requires considering both the inclusion of target sounds and exclusion of non-target sounds.
