An improved speech processor for cochlear implant based on active nonlinear model of biological cochlea

The purpose of this study was to improve speech perception performance of cochlear implant (CI) under noise by a speech processing strategy based on nonlinear time-varying filter model of biological cochlea, which is beneficial in preserving spectral cues for speech perception. A dual resonance nonlinear model was applied to implement this feature. Time-frequency analysis indicated that formant information was more clearly represented at the output of CI speech processor, especially under noise. Acoustic simulation and hearing experiment also showed the superiority of the proposed strategy in that vowel perception score was notably enhanced. It was also observed that the AN responses to the stimulation pulses produced by the proposed strategy encode the formant information faithfully. Since the proposed strategy can be employed in CI devices without modification of hardwares, a significant contribution for the improvement of speech perception capability of CI implantees is expected.