There has been significant progress in the music generation technique utilizing deep learning. However, it is still hard for musicians and artists to use these techniques in their daily music-making practice. This paper proposes a Variational Autoencoder\cite{Kingma2014}(VAE)-based rhythm generation system, in which musicians can train a deep learning model only by selecting target MIDI files, then generate various rhythms with the model. The author has implemented the system as a plugin software for a DAW (Digital Audio Workstation), namely a Max for Live device for Ableton Live. Selected professional/semi-professional musicians and music producers have used the plugin, and they proved that the plugin is a useful tool for making music creatively. The plugin, source code, and demo videos are available online.

中文翻译：

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使用基于变分自动编码器的节奏生成器的 AI 设计作为 DAW 插件，实现音乐制作的大众化

利用深度学习的音乐生成技术取得了重大进展。然而，对于音乐家和艺术家来说，在日常的音乐制作实践中仍然很难使用这些技术。本文提出了一种基于 Variational Autoencoder\cite{Kingma2014}(VAE) 的节奏生成系统，在该系统中，音乐家只需选择目标 MIDI 文件即可训练深度学习模型，然后使用该模型生成各种节奏。作者将该系统实现为 DAW（数字音频工作站）的插件软件，即 Ableton Live 的 Max for Live 设备。精选的专业/半专业音乐家和音乐制作人使用了该插件，他们证明该插件是创造性地制作音乐的有用工具。插件、源代码和演示视频可在线获取。