1. A digital sound recognition system, the system comprising: a sound input; program memory storing processor control code; working memory; non-volatile memory storing one or more statistical models of one or more target sounds, each of said statistical models having an associated set of probabilities; and a processor coupled to said sound input, to said working memory, and to said program memory for executing said processor control code, wherein said processor control code comprises code to: input sound data for a sound, the sound data defining frequency domain data, said frequency domain data defining an energy of said sound in a plurality of frequency ranges; perform a multiple component decomposition of said sound data by applying a succession of windows to said sound data to construct a time frequency representation of said sound data; determine a probability of said multiple component decomposition of said sound data fitting at least one of said one or more statistical models of said one or more target sounds, using said stored set of probabilities; and output sound identification data dependent on said determined probability; wherein said one or more statistical models of said one or more target sounds have states defined by a set of mean and covariance values for said one or more target sounds, generated from a time frequency representation of said one or more target sounds, and wherein said set of probabilities is related to a succession of said states characterising how a frequency distribution of said one or more target sounds represented by said one or more statistical models changes over time.