Modified Local Discriminant Bases and Its Application in Audio Feature Extraction

One of the major challenges in classification problems based on signal decomposition approach is to identify the right basis function and its derivatives that can provide optimal features to distinguish the classes. Local discriminant bases (LDB) algorithm is one such algorithm, which efficiently selects a set of significant basis functions from the library of orthonormal bases based on certain defined dissimilarity measure. In this paper, we modified the LDB algorithm and used the fisher criterion for feature selection. Finally, support vector machines is used as a classifier to identify music, pure speech and speech with music.