SPEECH-DISCRIMINATION VIA COCHLEAR IMPLANTS WITH 2 DIFFERENT DIGITAL SPEECH PROCESSING STRATEGIES - PRELIMINARY-RESULTS FOR 7 PATIENTS

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 classical channel vocoder concept whereby the time-averaged spectral energy of a number of logarithmically spaced frequency bands is transformed into appropriate 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 pitch extraction algorithm calculates the autocorrelation function of a lowpass-filtered segment of the speech signal and searches for a peak within a specified time window. A random pulse rate of about 150 to 250 Hz is used for unvoiced speech portions. The second approach (CIS, Continuous Interleaved Sampler) uses a stimulation pulse rate which is independent of the input signal. The algorithm scans continuously all specified frequency bands (typically between 4 and 22) and samples their energy levels. Evaluation experiments with 7 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 whereas 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. No final conclusions can yet be drawn. Optimization and fine-tuning of processing parameters for these coding strategies require more data both from speech identification and discrimination as well as psychophysical experiments.