通过抽样乐句加速音乐史料对比研究，提升分析效率与统计可靠性。
Beyond Bars: Distribution of Edit Operations in Historical Prints
- 从乐谱中抽样小节替代整体编码，降低数字化成本
- 以贝多芬《短歌集》为例，验证抽样方法在差异代表性上的表现
- 适合需大规模分析的历史音乐文献研究者
本文提出一种音乐学比较语料库研究的新方法，通过从乐谱中抽样小节而非完整编码整个语料库，显著减少耗时的数字化工作。针对样本代表性问题，评估了三种不同抽样策略，并以贝多芬《短歌集》作品33号为案例，找出最能反映差异的抽样方法。该方法可支持大规模分析，获得更具统计意义的研究结果。本研究不仅提升了历史音乐文献的可研究性，也为理解十九世纪编辑实践、推动学术编辑领域发展提供了重要支持。
原文摘要 · Abstract (English)
In this paper, we present a method for conducting comparative corpus studies in musicology that reduces the time-consuming digitization process. Instead of encoding whole corpora of musical sources, we suggest sampling bars from these sources. We address the challenge of selecting representative samples and evaluate three different sampling methods. We used Beethoven's Bagatelles Op. 33 as a case study to find the method that works best in finding samples representative with respect to differences. We believe that this approach offers significant value to musicological research by enabling large-scale analyses and thereby statistically sound results. Moreover, we believe our work to be a valuable step toward understanding nineteenth-century editorial practices and enriching the field of scholarly editing of historical musical works.
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