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      Expediting the identification of impaired channels in cochlear implants via analysis of speech-based confusion matrices.

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          Abstract

          There is significant variability in the benefit provided by cochlear implants to severely deafened individuals. The reasons why some subjects exhibit low speech recognition scores are unknown; however, underlying physiological or psychophysical factors may be involved. Certain phenomena, such as indiscriminable electrodes and nonmonotonic pitch rankings, might hint at limitations in the ability of individual channels in the cochlear implant and/or sensorineural pathway to convey speech information. In this paper, four approaches for analyzing the results of a simple listening test using speech stimuli are investigated for the purpose of targeting channels of concern in order for follow-on psychophysical experiments to correctly identify channels performing in an "impaired" or anomalous manner. Listening tests were first conducted with normal-hearing subjects and acoustic models simulating channel-specific anomalies. Results indicate that these proposed analyses perform significantly better than chance in providing information about the location of anomalous channels. Vowel and consonant confusion matrices from six cochlear implant subjects were also analyzed to test the robustness of the proposed analyses to variability intrinsic to cochlear implant data. The current study suggests that confusion matrix analyses have the potential to expedite the identification of impaired channels by providing preliminary information prior to exhaustive psychophysical testing.

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          Author and article information

          Journal
          IEEE Trans Biomed Eng
          IEEE transactions on bio-medical engineering
          0018-9294
          0018-9294
          Dec 2007
          : 54
          : 12
          Affiliations
          [1 ] Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708-0291, USA.
          Article
          18075035
          6b39c615-9f69-4e0f-b052-7985a2358d2b
          History

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