A rather general basic working hypothesis for cochlear implant research might be formulated as follows. Signal processing for cochlear implants should carefully select a subset of the total information contained in the sound signal and transform these elements into those physical stimulation parameters which can generate distinctive perceptions for the listener. Several new digital processing strategies have thus been implemented on a laboratory cochlear implant speech processor for the Nucleus 22-electrode system. One of the approaches (PES, pitch excited sampler) is based on the maximum peak channel vocoder concept whereby the spectral energy of a number of frequency bands is transformed into appropriate electrical stimulation parameters for up to 22 electrodes using a voice pitch synchronous pulse rate at any electrode. Another approach (CIS, continuous interleaved sampler) uses a maximally high pitch-independent stimulation pulse rate on a selected number of electrodes. As only one electrode can be stimulated at any instance of time, the rate of stimulation is limited by the required stimulus pulse widths (as determined individually for each subject) and some additional constraints and parameters which have to be optimized and fine tuned by psychophysical measurements. Evaluation experiments with 5 cochlear implant users resulted in significantly improved performance in consonant identification tests with the new processing strategies as compared with the subjects own wearable speech processors whereas improvements in vowel identification tasks were rarely observed. The pitch-synchronous coding (PES) resulted in worse performance compared to the coding without explicit pitch extraction (CIS). A great portion of the improvement is probably due to better transmission of sibilant and fricative (and to a lesser extent place of articulation) information.

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