利用Osu!游戏谱面数据构建高质量节拍标注集，拓展音乐信息检索研究资源。
Osu2MIR: Beat Tracking Dataset Derived From Osu! Data
- 从Osu!社区谱面中提取节拍与强拍标注，构建自动化处理流水线。
- 单节拍点或间距≥5秒的多节拍点谱面标注准确率高，适合直接使用。
- 适用于音乐节拍分析、跨风格数据集构建等研究，尤其适合非主流音乐类型。
本文探索将Osu!——一个由社区驱动的节奏类游戏——作为节拍与强拍标注的新来源。Osu!谱面由大量多元用户创建与优化，覆盖动漫、Vocaloid及游戏音乐等未被充分研究的音乐类型。我们提出一套从Osu!谱面中提取标注的流水线，并将其划分为有意义的子集。经人工分析发现，仅含一个节拍点或多个节拍点间距≥5秒的谱面能提供可靠标注，而间距小于5秒的谱面通常需额外筛选。同时，同一首歌的多重标注间表现出高度一致性。本研究证明Osu!数据可作为可扩展、多样化且由社区驱动的音乐信息检索（MIR）研究资源。我们公开了该流水线及高质量子集osu2beat2025，以支持后续研究：https://github.com/ziyunliu4444/osu2mir。
原文摘要 · Abstract (English)
In this work, we explore the use of Osu!, a community-based rhythm game, as an alternative source of beat and downbeat annotations. Osu! beatmaps are created and refined by a large, diverse community and span underrepresented genres such as anime, Vocaloid, and video game music. We introduce a pipeline for extracting annotations from Osu! beatmaps and partition them into meaningful subsets. Through manual analysis, we find that beatmaps with a single timing point or widely spaced multiple timing points (>=5 seconds apart) provide reliable annotations, while closely spaced timing points (<5 seconds apart) often require additional curation. We also observe high consistency across multiple annotations of the same song. This study demonstrates the potential of Osu! data as a scalable, diverse, and community-driven resource for MIR research. We release our pipeline and a high-quality subset osu2beat2025 to support further exploration: https://github.com/ziyunliu4444/osu2mir.
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