论文标题
感受音乐：自动为输入歌曲产生舞蹈
Feel The Music: Automatically Generating A Dance For An Input Song
论文作者
论文摘要
我们提出了一种通用计算方法，该方法使机器能够为任何输入音乐生成舞蹈。我们为“良好”舞蹈的直观，灵活的启发式方法编码：舞蹈的结构应与音乐的结构保持一致。这种灵活性使代理商可以发现创造性舞蹈。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力和鼓舞性。我们还评估了基于舞蹈的不同演示的创造力的看法如何变化。我们的代码可在https://github.com/purvaten/feel-the-music上找到。
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.
