Linking Sheet Music and Audio - Challenges and New Approaches

Verena Thomas, C. Fremerey, Meinard Müller, M. Clausen
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引用次数: 37

Abstract

Score and audio files are the two most important ways to represent, convey, record, store, and experience music. While score describes a piece of music on an abstract level using symbols such as notes, keys, and measures, audio files allow for reproducing a specific acoustic realization of the piece. Each of these representations reflects different facets of music yielding insights into aspects ranging from structural elements (e.g., motives, themes, musical form) to specific performance aspects (e.g., artistic shaping, sound). Therefore, the simultaneous access to score and audio representations is of great importance. In this paper, we address the problem of automatically generating musically relevant linking structures between the various data sources that are available for a given piece of music. In particular, we discuss the task of sheet music-audio synchronization with the aim to link regions in images of scanned scores to musically corresponding sections in an audio recording of the same piece. Such linking structures form the basis for novel interfaces that allow users to access and explore multimodal sources of music within a single framework. As our main contributions, we give an overview of the state-of-the-art for this kind of synchronization task, we present some novel approaches, and indicate future research directions. In particular, we address problems that arise in the presence of structural differences and discuss challenges when applying optical music recognition to complex orchestral scores. Finally, potential applications of the synchronization results are presented.
链接乐谱和音频-挑战和新方法
乐谱和音频文件是表现、传达、记录、存储和体验音乐的两种最重要的方式。乐谱用音符、琴键和小节等符号在抽象层面上描述一段音乐,而音频文件则可以再现这段音乐的具体声学实现。每一种表现都反映了音乐的不同方面,从结构元素(例如,动机,主题,音乐形式)到特定的表演方面(例如,艺术塑造,声音)。因此,同时获得乐谱和音频表示是非常重要的。在本文中,我们解决了在给定音乐片段可用的各种数据源之间自动生成音乐相关链接结构的问题。特别地,我们讨论了乐谱-音频同步的任务,目的是将扫描乐谱图像中的区域与同一件作品的音频记录中的音乐对应部分联系起来。这样的链接结构构成了新颖界面的基础,允许用户在单一框架内访问和探索多模态音乐来源。作为我们的主要贡献,我们概述了这种同步任务的最新技术,我们提出了一些新的方法,并指出了未来的研究方向。特别是,我们解决了存在结构差异时出现的问题,并讨论了将光学音乐识别应用于复杂管弦乐乐谱时面临的挑战。最后,对同步结果的应用前景进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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