Title: A Tutorial on Deep Learning for Music Information Retrieval,
Abstract: Following their success in Computer Vision and other areas, deep learning
techniques have recently become widely adopted in Music Information Retrieval
(MIR) research. However, the majority of works aim to adopt and assess methods
that have been shown to be effective in other domains, while there is still a
great need for more original research focusing on music primarily and utilising
musical knowledge and insight. The goal of this paper is to boost the interest
of beginners by providing a comprehensive tutorial and reducing the barriers to
entry into deep learning for MIR. We lay out the basic principles and review
prominent works in this hard to navigate the field. We then outline the network
structures that have been successful in MIR problems and facilitate the
selection of building blocks for the problems at hand. Finally, guidelines for
new tasks and some advanced topics in deep learning are discussed to stimulate
new research in this fascinating field.