@conference{9837541,

title = {Music Deep Learning: A Survey on Deep Learning Methods for Music Processing},

author = {Lazaros Alexios Iliadis and Sotirios P Sotiroudis and Kostas Kokkinidis and Panagiotis Sarigiannidis and Spiridon Nikolaidis and Sotirios K Goudos},

url = {https://www.researchgate.net/publication/333014972_Deep_Learning_Techniques_for_Music_Generation_-_A_Survey},

doi = {10.1109/MOCAST54814.2022.9837541},

isbn = {978-1-6654-6717-9},

year  = {2022},

date = {2022-06-08},

booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)},

pages = {1-4},

abstract = {Deep Learning has emerged as a powerful set of computational methods achieving great results in a variety of different tasks. Music signal processing, a field with rich commercial applications, seems to benefit too from this data-driven approach. In this paper a review of the state of the art Deep Learning methods applied on music signal processing is provided. A special focus is given in music information retrieval and music generation. In addition, possible future research directions are discussed.},

keywords = {Deep Learning, Music Generation, Music Information Retrieval, Music Signal Processing},

pubstate = {published},

tppubtype = {conference}

}