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Evaluation of dictionary for sparse coding in speech processing

As a promising technique, sparse coding has been widely used for the analysis, representation, compression, denoising and separation of speech. To represent a signal accurately and sparsely, a good dictionary which contains elemental signals is urgently desired and many methods have been proposed to obtain such a dictionary. However, there is a lack of reasonable evaluation methods to judge whether a dictionary is good enough. To solve this problem, we define a group of measures for the evaluation of a dictionary. These measures not only address the sparsity and reconstruction error in representation of a signal, but also consider the denoising and separating performances. Experiments show that the proposed measures can make reasonable evaluations.