1. A method for reducing noise in a noisy input signal, the method comprising: converting a frame of the noisy input signal into an input feature vector; obtaining a static-based prediction for a noise-reduced feature vector using a prior model of static aspects of clean signals; obtaining a dynamic-based prediction for the noise-reduced feature vector using a prior model of dynamic aspects of clean signals; combining the static-based prediction and the dynamic-based prediction to form at least part of a combined prediction; and multiplying the combined prediction by a measure of the probability of the input feature vector occurring to produce at least one component of the noise-reduced feature vector.