A revised version of the computational auditory signal processing and perception model (CASP, [1]) is proposed. CASP is a functional model designed for the prediction of data from various psychoacoustic conditions, including intensity discrimination, spectral and temporal masking and amplitude modulation detection and masking. The revised version of CASP proposed here introduces two main changes to the original model: (i) a more realistic, nonlinear inner hair cell stage replacing the simplified linear processing stage of the original model and (ii) an updated back-end processing that captures off-frequency listening through an automatic channel selection algorithm. The effects of these two modifications in the model are analysed in various signal detection and masking conditions, including intensity discrimination, forward masking as well as modulation detection using narrowband noise carriers. Model predictions are compared across model configurations and examined in terms of the internal representations of the signals at different stages of auditory processing within the model. The potential implications of the revised signal processing in the model on predictions of effects of sensorineural hearing loss are discussed.