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
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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。
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.
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