The source code for methods discussed in this paper is made available at. Finally, we discuss current challenges and the uncharted frontiers in this field. We also recommend preferred signal processing approaches for important audio equalization problems. Case studies are given in order to illustrate key concepts and how they are applied in practice. The application areas discussed herein are diverse, and include well-defined, solvable problems of filter design subject to constraints, as well as newly emerging challenges that touch on problems in semantics, perception and human computer interaction. Emphasis is placed on putting the range of approaches within a common mathematical and conceptual framework. Digital signal processing techniques for modifying the spectral balance in audio signals and applications of these techniques are reviewed, ranging from classic equalizers to emerging designs based on new advances in signal processing and machine learning. This review paper bridges those gaps, systemically providing a deep understanding of the problems and approaches in audio equalization, their relative merits and applications. The extent of research means that one often cannot identify the preferred technique for a particular problem. Audio equalization is a vast and active research area.
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