ASAP: a dataset of aligned scores and performances for piano transcription
ASAP: a dataset of aligned scores and performances for piano transcription
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发表时间：
2020-10
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通讯作者：
Francesco Foscarin;Andrew Mcleod;P. Rigaux;Florent Jacquemard;Masahiko Sakai
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作者：
Francesco Foscarin;Andrew Mcleod;P. Rigaux;Florent Jacquemard;Masahiko Sakai
在本文中，我们提出了对齐乐谱和演奏 (ASAP)：一个包含 222 个数字乐谱的新数据集，与西方古典钢琴音乐的 1068 场演奏（超过 92 小时）对齐。乐谱以配对的 MusicXML 文件和量化的 MIDI 文件的形式提供，演奏以配对的 MIDI 文件的形式提供，部分以录音的形式提供。乐谱和表演与强拍、节拍、拍号和调号注释保持一致。 ASAP 的实现得益于新的注释工作流程，该工作流程结合了分数分析和对齐算法，旨在减少手动注释的时间。据我们所知，该数据集本身是最大的，其中包括乐谱与 MIDI 和音频性能数据的对齐。因此，它对于各种 MIR 应用程序来说都是有用的资源，从那些针对完整音频到乐谱自动音乐转录任务的应用程序，到针对更具体方面的其他应用程序（例如，调号估计以及来自 MIDI 和音频表示的节拍或强拍跟踪）。
In this paper we present Aligned Scores and Performances (ASAP): a new dataset of 222 digital musical scores aligned with 1068 performances (more than 92 hours) of Western classical piano music. The scores are provided as paired MusicXML files and quantized MIDI files, and the performances as paired MIDI files and partially as audio recordings. Scores and performances are aligned with downbeat, beat, time signature, and key signature annotations. ASAP has been obtained thanks to a new annotation workflow that combines score analysis and alignment algorithms, with the goal of reducing the time for manual annotation. The dataset itself is, to our knowledge, the largest that includes an alignment of music scores to MIDI and audio performance data. As such, it is a useful resource for a wide variety of MIR applications, from those that target the complete audio-to-score Automatic Music Transcription task, to others that target more specific aspects (e.g., key signature estimation and beat or downbeat tracking from both MIDI and audio representations).