Predicting Speech Recognition Using the Speech Intelligibility Index and Other Variables for Cochlear Implant Users

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dc.contributor.authorLee, Sungmin
dc.contributor.authorMendel, L. L.
dc.contributor.authorBidelman, G. M.
dc.contributor.utdAuthorLee, Sungmin
dc.date.accessioned2020-03-19T19:33:59Z
dc.date.available2020-03-19T19:33:59Z
dc.date.issued2019-05-13
dc.descriptionSupplementary material is available on publisher's website. Use the DOI link below.
dc.description.abstractPurpose Although the speech intelligibility index (SII) has been widely applied in the field of audiology and other related areas, application of this metric to cochlear implants (CIs) has yet to be investigated. In this study, SIIs for CI users were calculated to investigate whether the SII could be an effective tool for predicting speech perception performance in a population with CI. Method Fifteen pre- and postlingually deafened adults with CI participated. Speech recognition scores were measured using the AzBio sentence lists. CI users also completed questionnaires and performed psychoacoustic (spectral and temporal resolution) and cognitive function (digit span) tests. Obtained SIIs were compared with predicted SIIs using a transfer function curve. Correlation and regression analyses were conducted on perceptual and demographic predictor variables to investigate the association between these factors and speech perception performance. Result Because of the considerably poor hearing and large individual variability in performance, the SII did not predict speech performance for this CI group using the traditional calculation. However, new SII models were developed incorporating predictive factors, which improved the accuracy of SII predictions in listeners with CI. Conclusion Conventional SII models are not appropriate for predicting speech perception scores for CI users. Demographic variables (aided audibility and duration of deafness) and perceptual-cognitive skills (gap detection and auditory digit span outcomes) are needed to improve the use of the SII for listeners with CI. Future studies are needed to improve our CI-corrected SII model by considering additional predictive factors. Supplemental Material https://doi.org/10.23641/asha.8057003.
dc.description.departmentSchool of Behavioral and Brain Sciences
dc.description.sponsorshipNational Institute on Deafness and Other Communication Disorders Award R01DC016267
dc.identifier.bibliographicCitationLee, S., L. L. Mendel, and G. M. Bidelman. 2019. "Predicting Speech Recognition Using the Speech Intelligibility Index and Other Variables for Cochlear Implant Users." Journal of Speech, Language, and Hearing Research : JSLHR 62(5): 1517-1531, doi: 10.1044/2018_JSLHR-H-18-0303
dc.identifier.issn1558-9102
dc.identifier.issue5
dc.identifier.urihttp://dx.doi.org/10.1044/2018_JSLHR-H-18-0303
dc.identifier.urihttps://hdl.handle.net/10735.1/7415
dc.identifier.volume62
dc.language.isoen
dc.publisherAmerican Speech-Language-Hearing Association
dc.rights©2019 American Speech-Language-Hearing Association
dc.source.journalJournal of Speech, Language, and Hearing Research : JSLHR
dc.subjectCochlear implants
dc.subjectSpeech Intelligibility Index
dc.subjectSpeech perception
dc.titlePredicting Speech Recognition Using the Speech Intelligibility Index and Other Variables for Cochlear Implant Users
dc.type.genrearticle

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