A biologically realistic neural network model is proposed for the binaural processing of interaural-time and level cues that closely resembles computational schemes suggested for atereopsis in vision. The network requires no neural delay lines to generate such attributes of binaural hearing as the lateralization of all frequencies, and the detection and enhancement of noisy signals. The two-dimensional network measures interaural differences by detecting the spatial disparities between the instantaneous outputs of the two ears. It achieves this by comparing systematically at various horizontal shifts, the spatiotemporal responses of the tonotopically ordered array of auditory-nerve- fibers. An alternative view of the network operation is that it computes approximately the cross-correlation between the responses of the two cochlei by combining an ipsilateral input at a given CF with contralateral inputs from locally off-CF locations. Thus, the network utilizes the delays already present in the travelling waves of the basilar membrane to extract the correlation function. Simulations of the network operation with various signals are presented; Physiological arguments in support of this scheme are also discussed.