Extended model variety analysis for integrated processing and understanding of signals

The authors extend their previous work (Nawab and Lesser, 1991; Weiss et al., 1991) on model variety analysis of a signal processing algorithm with respect to the class of all input signals that may potentially arise in a given signal understanding application. This analysis has two related objectives. The first objective is to partition the set of all possible signals in the application domain into two sets according to whether each signal is correctly or incorrectly processed by the signal processing algorithm under consideration. The second objective of model variety analysis is to characterize the nature of the distortions in the signal processing output for the cases where the input signal is incorrectly processed. The results of model variety analysis are useful for designing signal understanding systems for applications where it is necessary for the signal processing to be carried out in a situation-dependent manner. Model variety analysis and its usefulness for the design of signal understanding systems are illustrated through examples involving the use of short-time Fourier transform (STFT) processing for a sound understanding application