L. Iliadis, S. Sotiroudis, K. Kokkinidis, P. Sarigiannidis, S. Nikolaidis, S. Goudos
{"title":"Music Deep Learning: A Survey on Deep Learning Methods for Music Processing","authors":"L. Iliadis, S. Sotiroudis, K. Kokkinidis, P. Sarigiannidis, S. Nikolaidis, S. Goudos","doi":"10.1109/mocast54814.2022.9837541","DOIUrl":null,"url":null,"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.","PeriodicalId":122414,"journal":{"name":"2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"34 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mocast54814.2022.9837541","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
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.