Optimised soundprint selection for identification in audio streams

An improved iterative method for the selection of reference soundprints from a set of sound records to be identified is presented. The soundprints applied to reliable streaming audio identification should have maximum dissimilarity to each other. As the first trial of the iteration, a set of soundprints is randomly selected according to a grid placed on the records. To the accepted set, a further local refinement process is applied using the quadratic local approximations of the Euclidean distance between the soundprints. A large number of measurements have shown that the method significantly improves the reliability of real-time monitoring