A neural network model is proposed for the binaural processing of interaural-time and level cues. The two-dimensional network measures interaural differences by detecting the spatial disparities between the instantaneous outputs of the two ears. 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. 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 cochleas by combining an ipsilateral input at a given characteristic frequency (CF) with contralateral inputs from locally off-CF locations. Thus the network utilizes the delays already present in the traveling waves of the basilar membrane to extract the correlation function. Simulations of the network operation with various signals are presented as are comparisons to computational schemes suggested for stereopsis in vision. Physiological arguments in support of this scheme are also discussed.