We present a general computational approach that enables a machine to generate a dance for any input music. We encode intuitive, flexible heuristics for what a 'good' dance is: the structure of the dance should align with the structure of the music. This flexibility allows the agent to discover creative dances. Human studies show that participants find our dances to be more creative and inspiring compared to meaningful baselines. We also evaluate how perception of creativity changes based on different presentations of the dance. Our code is available at https://github.com/purvaten/feel-the-music.

中文翻译：

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感受音乐：自动为输入歌曲生成舞蹈

我们提出了一种通用的计算方法，使机器能够为任何输入音乐生成舞蹈。我们对什么是“好”舞蹈进行了直观、灵活的启发式编码：舞蹈的结构应该与音乐的结构保持一致。这种灵活性允许代理发现创造性的舞蹈。人类研究表明，与有意义的基线相比，参与者发现我们的舞蹈更具创造性和启发性。我们还评估了根据舞蹈的不同表现如何改变对创造力的看法。我们的代码可在 https://github.com/purvaten/feel-the-music 获得。