This chapter presents an overview of dictionary learning-based speech enhancement methods. Specifically, we review the existing algorithms that employ sparse representation (SR), nonnegative matrix factorization (NMF), and their variations applying for speech enhancement. We emphasize that there are two stages in a speech enhancement system, namely learning dictionary and enhancement. The two scenarios of learning dictionary process, offline and online, are discussed carefully as well. We finally present some evaluation methods and suggest the future lines of work.
Part of the book: Active Learning