多模态音乐信息处理与检索:调查与未来挑战

Federico Simonetta, S. Ntalampiras, F. Avanzini
{"title":"多模态音乐信息处理与检索:调查与未来挑战","authors":"Federico Simonetta, S. Ntalampiras, F. Avanzini","doi":"10.1109/MMRP.2019.00012","DOIUrl":null,"url":null,"abstract":"Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, mid-level representations, motion and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval, and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years.","PeriodicalId":441469,"journal":{"name":"2019 International Workshop on Multilayer Music Representation and Processing (MMRP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"42","resultStr":"{\"title\":\"Multimodal Music Information Processing and Retrieval: Survey and Future Challenges\",\"authors\":\"Federico Simonetta, S. Ntalampiras, F. Avanzini\",\"doi\":\"10.1109/MMRP.2019.00012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, mid-level representations, motion and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval, and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years.\",\"PeriodicalId\":441469,\"journal\":{\"name\":\"2019 International Workshop on Multilayer Music Representation and Processing (MMRP)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"42\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Workshop on Multilayer Music Representation and Processing (MMRP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMRP.2019.00012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Workshop on Multilayer Music Representation and Processing (MMRP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMRP.2019.00012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 42

摘要

为了提高在各种音乐信息处理任务中的表现,最近的研究利用了不同的模式来捕捉音乐的不同方面。这些形式包括录音、象征性乐谱、中级表现、动作和手势数据、录像、编辑或文化标签、歌词和专辑封面艺术。本文批判性地回顾了音乐信息处理和检索中采用的各种方法,并强调了多模态算法如何帮助音乐计算应用。首先,我们根据它们所涉及的应用对相关文献进行分类。随后,我们分析了现有的信息融合方法,并总结了音乐信息检索和声音与音乐计算研究团体在未来几年应该关注的一系列挑战。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multimodal Music Information Processing and Retrieval: Survey and Future Challenges
Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, mid-level representations, motion and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval, and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years.
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
自引率
0.00%
发文量
0
期刊最新文献
On the Use of U-Net for Dominant Melody Estimation in Polyphonic Music State of the Art and Perspectives in Multi-Layer Formats for Music Representation 2019 International Workshop on Multilayer Music Representation and Processing MMRP 2019 Reviewers MMRP 2019 Message from the General Chair MMRP 2019
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1