The recognition of sentences in noise by normal-hearing listeners using simulations of cochlear-implant signal processors with 6-20 channels

Abstract

Sentences were processed through simulations of cochlear-implant signal processors with 6, 8, 12, 16, and 20 channels and were presented to normal-hearing listeners at +2 db S/N and at -2 db S/N. The signal-processing operations included bandpass filtering, rectification, and smoothing of the signal in each band, estimation of the rms energy of the signal in each band (computed every 4 ms), and generation of sinusoids with frequencies equal to the center frequencies of the bands and amplitudes equal to the rms levels in each band. The sinusoids were summed and presented to listeners for identification. At issue was the number of channels necessary to reach maximum performance on tests of sentence understanding. At +2 dB S/N, the performance maximum was reached with 12 channels of stimulation. At -2 dB S/N, the performance maximum was reached with 20 channels of stimulation. These results, in combination with the outcome that in quiet, asymptotic performance is reached with five channels of stimulation, demonstrate that more channels are needed in noise than in quiet to reach a high level of sentence understanding and that, as the S/N becomes poorer, more channels are needed to achieve a given level of performance.