Sparse Modeling with Applications to Speech Processing: A Survey

Abstract

Nowadays, there has been a growing interest in the study of sparse approximation of signals. Using an over-complete dictionary consisting of prototype signals or atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and include compression, source separation, enhancement, and regularization in inverse problems, feature extraction, and more. This article introduces a literature review of sparse coding applications in the field of speech processing.