论文标题
用用户提供的结构环境填充旋律
Melody Infilling with User-Provided Structural Context
论文作者
论文摘要
本文提出了一种基于变压器的新型模型，用于音乐得分填充，以产生一段音乐段落，以填补给定过去和将来的上下文之间的差距。尽管现有的填充方法可以生成一段段落，该段落与给定上下文平稳地连接，但它们没有考虑到音乐的音乐形式或结构，因此可能会产生过度平滑的结果。为了解决这个问题，我们提出了一种结构感知的调节方法，该方法采用新颖的注意力选择模块向变压器提供与用户提供的结构相关信息以进行填充。通过客观和主观评估，我们表明所提出的模型可以有效地利用结构信息，并以更高质量的流行风格产生旋律，而不是现有的两个结构 - 不合稳定的填充模型。
This paper proposes a novel Transformer-based model for music score infilling, to generate a music passage that fills in the gap between given past and future contexts. While existing infilling approaches can generate a passage that connects smoothly locally with the given contexts, they do not take into account the musical form or structure of the music and may therefore generate overly smooth results. To address this issue, we propose a structure-aware conditioning approach that employs a novel attention-selecting module to supply user-provided structure-related information to the Transformer for infilling. With both objective and subjective evaluations, we show that the proposed model can harness the structural information effectively and generate melodies in the style of pop of higher quality than the two existing structure-agnostic infilling models.
