用极低误报率快速发现海量文献中的乐谱
DEMUN: Fast and accurate discovery of music notation in very large collections
- 两阶段轻量级检测器，专为大规模文档设计
- 处理400万图像仅0.015%误报，发现1500页新乐谱
- 适合研究音乐生活史的学者，尤其关注非专业文献
大量书面音乐遗产被保存在图书馆、博物馆和档案馆等机构中。由于收藏结构，乐谱通常集中在特定类别中，配有可检索的元数据。但若研究音乐生活而非单个作品时，相关文档往往出现在教科书、报纸、期刊、小册子等广泛流传的非专业文献中。这些文件未被标注为音乐资料，在大型馆藏中虽总量可观，但分布极为稀疏。人工查找不现实，自动化发现需具备极低误报率且高效运行。本文提出DEMUN：一种两阶段轻量级乐谱检测器，误报率仅为0.015%。在处理一国规模图书馆的400万张图像时，共发现1,500页含乐谱的页面，推测整个馆藏可能包含2万至3万份未标记的音乐生活类文献。
原文摘要 · Abstract (English)
Much of written musical heritage is preserved and digitised at memory institutions: libraries, museums, and archives. Owing to their collection structures, sheet music tends to be concentrated in large subsets that are defined as collections of music, with corresponding metadata that makes the music findable. However, when studying musical life as opposed to individual works, relevant documents often lie outside of these specialised collections: in textbooks, newspapers, other periodicals, pamphlets, and other documents with extensive circulation. But these documents are typically not catalogued as musical documents, and though there may be a lot of such documents overall, in large library collections, they are still extremely sparse. Manual discovery is thus unfeasible. Automated discovery requires an extremely low false positive rate in order to be useful, and must also operate quickly. We present DEMUN: a two-stage lightweight detector of music notation with a false positive rate of 0.015 %. In the test scenario, 4 million images of a national-scale library were processed, out of which 1,500 pages with music notation were discovered, suggesting the entire collection may contain up to 20-30,000 unmarked documents of musical life.
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