The study will investigate the perception of the sources of familiar environmental sounds processed through a simulated cochlear implant with a varying number of frequency channels. Familiar sounds include human and animal vocalizations (e.g., baby cry, dog bark), nature sounds (e.g., rain, wind), mechanical sounds (e.g., engines, footsteps), and electronic sounds (e.g., alarms, telephones). Results will be used to (1) establish the minimal number of channels needed for source identification for a large number of environmental sounds, (2) to determine variability among individual environmental sounds in the minimal number of channels needed for source identification, (3) to differentiate and classify individual environmental sounds based on the number of channels needed for source identification, (4) to investigate how listeners' perceptual dimensions change as a function of varying number of channels as revealed by Multidimensional scaling. Stimuli will be obtained by processing original environmental sound recordings through a simulated cochlear implant with different numbers of frequency channels, and presented to normally hearing listeners for source identification. The findings of the study will be relevant to cochlear implant design, and will provide an empirical basis for a theory of environmental sound perception. [unreadable] [unreadable]