An improved speech processing strategy for cochlear implants based on an active nonlinear filterbank model of the biological cochlea.

Abstract

The purpose of this study was to improve the speech processing strategy for cochlear implants (CIs) based on a nonlinear time-varying filter model of a biological cochlea. The level-dependent frequency response characteristic of the basilar membrane is known to produce robust formant representation and speech perception in noise. A dual resonance nonlinear (DRNL) model was adopted because it is simpler than other adaptive nonlinear models of the basilar membrane and can be readily incorporated into the CI speech processor. Spectral analysis showed that formant information is more saliently represented at the output of the proposed CI speech processor compared to the conventional strategy in noisy conditions. Acoustic simulation and hearing experiments showed that the DRNL-based nonlinear strategy improves speech performance in a speech-spectrum-shaped noise.