Recognition of sentences in noise by normal-hearing listeners using simulations of speak-type cochlear implant signal processors.

To assess whether more channels are needed to understand speech in noise than in quiet, we processed speech in a manner similar to that of spectral peak-like cochlear implant processors and presented it at a +2-dB signal-to-noise ratio to normal-hearing listeners for identification. The number of analysis filters varied from 8 to 16, and the number of maximum channel amplitudes selected in each cycle varied from 2 to 16. The results show that more channels are needed to understand speech in noise than in quiet, and that high levels of speech understanding can be achieved with 12 channels. Selecting more than 12 channel amplitudes out of 16 channels did not yield significant improvements in recognition performance.