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arXiv 2004.01525eess.AScs.LGcs.SD

Towards democratizing music production with AI-Design of Variational Autoencoder-based Rhythm Generator as a DAW plugin

Keio University(庆应义塾大学)

Nao Tokui

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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