论文标题
垂直 - 霍森塔尔的结构化注意，以与和弦产生音乐
Vertical-Horizontal Structured Attention for Generating Music with Chords
论文作者
论文摘要
在本文中，我们提出了一个基于变异自动编码器（VAE）的轻量级音乐生成模型，并引起了结构化的注意。生成音乐与生成文本不同，因为带有和弦的旋律使听众具有区别的复音感觉。在音乐中，由多个音符组成的和弦来自多种乐器的混合物或单个乐器的多个键的组合。我们将研究重点放在后者上。我们的模型不仅捕获了时间关系，还捕获了密钥之间的结构关系。实验结果表明，在捕获和弦中捕获笔记时，我们的模型比基线音乐的性能更好。此外，我们的方法符合音乐理论，因为它保持了五分之一圆的配置，将主要键和小键与间隔向量区分开，并在音乐短语之间表现出有意义的结构。
In this paper, we propose a lightweight music-generating model based on variational autoencoder (VAE) with structured attention. Generating music is different from generating text because the melodies with chords give listeners distinguished polyphonic feelings. In a piece of music, a chord consisting of multiple notes comes from either the mixture of multiple instruments or the combination of multiple keys of a single instrument. We focus our study on the latter. Our model captures not only the temporal relations along time but the structure relations between keys. Experimental results show that our model has a better performance than baseline MusicVAE in capturing notes in a chord. Besides, our method accords with music theory since it maintains the configuration of the circle of fifths, distinguishes major and minor keys from interval vectors, and manifests meaningful structures between music phrases.
