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 th an in quiet, we processed speech in a manner similar to that of spectral pe ak-like cochlear implant processors and presented it at a +2-dB signal-to-n oise ratio to normal-hearing listeners for identification. The number of an alysis filters varied from 8 to 16, and the number of maximum channel ampli tudes selected in each cycle varied from 2 to 16. The results show that mor e channels are needed to understand speech in noise than in quiet, and that high levels of speech understanding can be achieved with 12 channels. Sele cting more than 12 channel amplitudes out of 16 channels did not yield sign ificant improvements in recognition performance.