MODULATION DETECTION AND DISCRIMINATION WITH 3-COMPONENT SIGNALS

In an attempt to study the processing of amplitude and frequency modulation (AM and FM), detection and discrimination tasks using mixed modulation (MM) signals were performed. Modulation detection thresholds were obtained for three-component signals that span the parameter space between AM and quasi-FM. A single-cue modulation detection model predicts the thresholds with reasonable accuracy. If one assumes that the AM and FM components are extracted separately, thresholds are also well predicted if the d' of the MM signals is equal to the sum of the separate d's of the AM and FM components (two-cue summation model). This could arise from common internal noise that puts the AM and FM information along a single decision axis. A modulation discrimination task was then examined in which the subjects discriminate between signals with both different modulation depths and different modulation types. The single-cue model predicts performance well. In order for the two-cue model to predict the results, the AM and FM cues must be combined into a single statistic before a decision can be made; the listener cannot process the cues separately.