Many of the music generation systems based on neural networks are fully autonomous and do not offer control over the generation process. In this research, we present a controllable music generation system in terms of tonal tension. We incorporate two tonal tension measures based on the Spiral Array Tension theory into a variational autoencoder model. This allows us to control the direction of the tonal tension throughout the generated piece, as well as the overall level of tonal tension. Given a seed musical fragment, stemming from either the user input or from directly sampling from the latent space, the model can generate variations of this original seed fragment with altered tonal tension. This altered music still resembles the seed music rhythmically, but the pitch of the notes are changed to match the desired tonal tension as conditioned by the user.

中文翻译：

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一种由音调张力控制的用于音乐生成的变分自动编码器

许多基于神经网络的音乐生成系统是完全自主的，不提供对生成过程的控制。在这项研究中，我们在音调张力方面提出了一个可控的音乐生成系统。我们将基于螺旋阵列张力理论的两个音调张力测量合并到一个变分自动编码器模型中。这使我们能够控制整个生成乐曲的音调张力的方向，以及音调张力的整体水平。给定一个种子音乐片段，源于用户输入或直接从潜在空间采样，该模型可以生成这个原始种子片段的变化，具有改变的音调张力。这个改过的音乐在节奏上还是很像种子音乐的，