音乐深度学习:音乐处理的深度学习方法综述

2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST) Pub Date : 2022-06-08 DOI:10.1109/mocast54814.2022.9837541

L. Iliadis, S. Sotiroudis, K. Kokkinidis, P. Sarigiannidis, S. Nikolaidis, S. Goudos

{"title":"音乐深度学习:音乐处理的深度学习方法综述","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":"{\"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}","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

摘要

深度学习已经成为一套强大的计算方法，在各种不同的任务中取得了巨大的成果。音乐信号处理，一个有着丰富商业应用的领域，似乎也从这种数据驱动的方法中受益。本文综述了深度学习方法在音乐信号处理中的应用现状。重点介绍了音乐信息检索和音乐生成。并对未来可能的研究方向进行了讨论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Music Deep Learning: A Survey on Deep Learning Methods for Music Processing

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)

自引率

0.00%

发文量