A model for predicting the audibility of time-varying signals in background sounds is described. The model requires the calculation of time-varying excitation patterns for the signal and background, using the methods described elsewhere. A quantity called instantaneous partial loudness (IPL) is calculated from the excitation patterns. The estimates of IPL, which are updated every 1 ms, are used to calculate the short-term partial loudness (STPL) using a form of running average similar to an automatic gain control system. It is assumed that the audibility of the signal is monotonically related to the average value of the STPL over the duration of the signal. In experiment 1 thresholds were measured for detecting a 1-kHz sinusoid in four different samples each of white and pink “frozen” noise. The results were used to determine the average value of the STPL required for threshold. In experiment 2 the model was evaluated by measuring detection thresholds for nine signal types in six backgrounds (54 combinations), using a two-alternative forced-choice task. The backgrounds were chosen to be relatively steady (such as traffic noise). The correlation between the measured masked thresholds and those predicted by the model was 0.94. The root-meansquare difference between the thresholds obtained and those predicted was 3 dB. In experiment 3 psychometric functions were measured for the detection of five signals in five backgrounds (five pairs), using a two-alternative forced-choice task. Experiment 4 used the same signals and backgrounds, but psychometric functions were measured using a singleinterval yes–no task. The results of experiments 3 and 4 were used to construct functions relating signal detectability d to the average value of the STPL.
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