Mode classification and natural units in plainchant

B. Cornelissen, W. Zuidema, J. Burgoyne
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引用次数: 5

Abstract

Many musics across the world are structured around multiple modes, which hold a middle ground between scales and melodies. We study whether we can classify mode in a corpus of 20,865 medieval plainchant melodies from the Cantus database. We revisit the traditional ‘textbook’ classification approach (using the final, the range and initial note) as well as the only prior computational study we are aware of, which uses pitch profiles. Both approaches work well, but largely reduce modes to scales and ignore their melodic character. Our main contribution is a model that reaches 93–95% F1 score on mode classification, compared to 86– 90% using traditional pitch-based musicological methods. Importantly, it reaches 81–83% even when we discard all absolute pitch information and reduce a melody to its contour. The model uses tf–idf vectors and strongly depends on the choice of units: i.e., how the melody is segmented. If we borrow the syllable or word structure from the lyrics, the model outperforms all of our baselines. This suggests that, like language, music is made up of ‘natural’ units, in our case between the level of notes and complete phrases, a finding that may well be useful in other musics.
平调中的模式分类与自然单位
世界上许多音乐都是围绕着多个调式来构建的,这些调式在音阶和旋律之间保持着一个中间地带。我们研究是否可以分类模式的语料库20865中世纪单声圣歌的旋律从旋律数据库。我们重新审视了传统的“教科书”分类方法(使用终音、音域和初始音符),以及我们所知道的唯一一个使用音高剖面的先前计算研究。这两种方法都很有效,但在很大程度上将调式降为音阶,而忽略了它们的旋律特征。我们的主要贡献是一个模型在调式分类上达到93-95%的F1得分,而使用传统的基于音高的音乐学方法则为86 - 90%。重要的是,即使我们放弃所有绝对音高信息并将旋律减少到其轮廓,它也能达到81-83%。该模型使用tf-idf向量,并且强烈依赖于单元的选择:即旋律如何分割。如果我们从歌词中借用音节或单词结构,该模型的表现优于我们所有的基线。这表明,像语言一样,音乐是由“自然”单位组成的,在我们的例子中,在音符和完整的乐句之间,这一发现可能对其他音乐很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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