A correlation technique was used to assess the decision rules of three listeners in two cases of spectral-shape discrimination tasks. In one case the signal frequency was fixed, and in the other it was randomly varied within each block of trials. In order to estimate the decision rule of the listeners, the experimenter superimposed random level perturbations on each frequency component upon each stimulus presentation. Over many trials, correlation coefficients were computed between the random perturbations and the binary responses of the listeners, and were expressed as a function of signal level. For both the fixed- and random-signal cases, the measured correlation functions were in reasonably good agreement with those predicted based on the likelihood-ratio decision rules. Thus the listeners appeared to use information nearly optimally in discriminating spectral shapes. This investigation demonstrated that the correlation technique can be used to reveal the decision rules for cases where the decision statistics are nonlinear functions of the observations.