Guitar Tab Mining, Analysis and Ranking
Guitar Tab Mining, Analysis and Ranking
复制标题
吉他谱挖掘、分析和排名
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
S. Dixon
中科院分区：
文献类型：
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作者：
R. Macrae;S. Dixon
有超过450万个制表符和和弦序列（统称为制表符），网络上有大量的非标准化文本文件中的手写注释乐谱。这些分数通常是容易出错和不完整的，并且选项卡集合包含许多重复项，使得检索高质量的选项卡变得困难。尽管如此，标签是迄今为止在互联网上分享音乐指令最流行的方式。我们已经开发了使用文本分析和对齐的工具，用于自动检索，解释和分析这些选项卡，以便从众多可用的选项卡中筛选和估计最准确的选项卡。我们表明，标准的手段排名标签，如搜索引擎排名或用户评级，有一个标签的准确性，一个更好的排名方法是使用功能，如标签之间的并发性相同的歌曲，几乎没有相关性。我们还比较了顶级标签的质量与最先进的和弦转录输出，发现后者提供了一个更可靠的和弦符号的来源，准确率比排名手注释高10%。
With over 4.5 million tablatures and chord sequences (collectively known as tabs), the web holds vast quantities of hand annotated scores in non-standardised text files. These scores are typically error-prone and incomplete, and tab collections contain many duplicates, making retrieval of high quality tabs difficult. Despite this, tabs are by far the most popular means of sharing musical instructions on the internet. We have developed tools that use text analysis and alignment for the automatic retrieval, interpretation and analysis of such tabs in order to filter and estimate the most accurate tabs from the multitude available. We show that the standard means of ranking tabs, such as search engine ranks or user ratings, have little correlation with the accuracy of a tab and that a better ranking method is to use features such as the concurrency between tabs of the same song. We also compare the quality of top-ranked tabs with state-of-the-art chord transcription output and find that the latter provides a more reliable source of chord symbols with an accuracy rate 10% higher than the ranked hand annotations.