Dillier N, Bögli H, Spillmann T
Department of Otorhinolaryngology, University Hospital, Zurich, Switzerland.
Prog Brain Res. 1993;97:301-11. doi: 10.1016/s0079-6123(08)62290-6.
The following processing strategies have been implemented on an experimental laboratory system of a cochlear implant digital speech processor (CIDSP) for the Nucleus 22-channel cochlear prosthesis. The first approach (PES, Pitch Excited Sampler) is based on the maximum peak channel vocoder concept whereby the time-varying spectral energy of a number of frequency bands is transformed into electrical stimulation parameters for up to 22 electrodes. The pulse rate at any electrode is controlled by the voice pitch of the input speech signal. The second approach (CIS, Continuous Interleaved Sampler) uses a stimulation pulse rate which is independent of the input signal. The algorithm continuously scans all specified frequency bands (typically between four and 22) and samples their energy levels. As only one electrode can be stimulated at any instance of time, the maximally achievable rate of stimulation is limited by the required stimulus pulse widths (determined individually for each subject) and some additional constraints and parameters. A number of variations of the CIS approach have, therefore, been implemented which either maximize the number of quasi-simultaneous stimulation channels or the pulse rate on a reduced number of electrodes. Evaluation experiments with five experienced cochlear implant users showed significantly better performance in consonant identification tests with the new processing strategies than with the subjects' own wearable speech processors; improvements in vowel identification tasks were rarely observed. Modifications of the basic PES- and CIS strategies resulted in large variations of identification scores. Information transmission analysis of confusion matrices revealed a rather complex pattern across conditions and speech features. Optimization and fine-tuning of processing parameters for these coding strategies will require more data both from speech identification and discrimination evaluations and from psychophysical experiments.
