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  • Research Article
  • Open Access

Prediction of Speech Recognition in Cochlear Implant Users by Adapting Auditory Models to Psychophysical Data

EURASIP Journal on Advances in Signal Processing20092009:175243

  • Received: 15 December 2008
  • Accepted: 18 June 2009
  • Published:


Users of cochlear implants (CIs) vary widely in their ability to recognize speech in noisy conditions. There are many factors that may influence their performance. We have investigated to what degree it can be explained by the users' ability to discriminate spectral shapes. A speech recognition task has been simulated using both a simple and a complex models of CI hearing. The models were individualized by adapting their parameters to fit the results of a spectral discrimination test. The predicted speech recognition performance was compared to experimental results, and they were significantly correlated. The presented framework may be used to simulate the effects of changing the CI encoding strategy.


  • Complex Model
  • Quantum Information
  • Speech Recognition
  • Recognition Task
  • Encode Strategy

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Authors’ Affiliations

Sound and Image Processing Lab, KTH, 10044 Stockholm, Sweden


© S. Stadler and A. Leijon. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.