The Sticky Riff: Quantifying the Melodic Identities of Medieval Modes

IF 0.6 0 MUSIC
K. Helsen, Mark Daley, Jake Schindler
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Abstract

Andrew Hughes' Late Medieval Liturgical Offices afforded chant scholarship more melodies than it knew what to do with. Until now, chant scholarship involving 'Big Data' usually meant comparing individual feasts to the whole corpus or looking at general trends with respect to 'word painting' or stereotyped cadences. New research presented here, using n-gram analysis, networks, and Recurrent Neural Networks (RNN) looks to the nature of the gestural components of the melodies themselves. By isolating the notes preceding, and proceeding from, the naturally occurring semitones in the medieval church modes, we find significant recurrence of particular phrases, or riffs, which we propose could have been used to help 'build modes' from the inside out. Special care needed to be brought to the question of assumed B-flats that were not given explicitly in the manuscripts represented in Hughes' work. Understanding modes not as 'scales' but as a collection of associated smaller musical gestures, has resulted in a set of recurring riffs that appear as the identifiers of their larger contexts and confirming the influence of an earlier, oral / aural culture on these late medieval chants where musical literacy was expected.  
粘性里夫:量化中世纪模式的旋律同一性
Andrew Hughes的中世纪晚期文学办公室为圣歌奖学金提供了比它所知道的更多的旋律。到目前为止,涉及“大数据”的圣歌学术通常意味着将个人盛宴与整个语料库进行比较,或者观察“单词绘画”或刻板节奏的总体趋势。这里提出的新研究,使用n-gram分析、网络和递归神经网络(RNN),着眼于旋律本身的手势成分的性质。通过分离中世纪教堂模式中自然出现的半音之前和之后的音符,我们发现特定短语或即兴段的显著重复,我们认为这些短语或即兴片段可以用来帮助从内到外“构建模式”。需要特别注意的是,假设的B平面问题在休斯作品中的手稿中没有明确给出。将模式理解为一组相关的较小的音乐手势,而不是“音阶”,导致了一组重复出现的即兴段,这些即兴段作为其较大上下文的标识符,并证实了早期口头/听觉文化对这些中世纪晚期圣歌的影响,在这些圣歌中,人们期望音乐素养。
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