论文标题
自动检测DJ混合的提示点
Automatic Detection of Cue Points for DJ Mixing
论文作者
论文摘要
提示点的自动识别是音乐缩略图，混搭生成和DJ混合等多样化的应用中的一项核心任务。我们的重点在于电子舞蹈音乐和特定的提示点，即“开关点”，这使得可以在轨道之间自动构建过渡，从而模仿专业DJ的工作。我们提出了一种检测开关点的方法，该方法体现了我们从专业DJ的访谈中确定的一些一般规则；这些规则的实施基于提取和新颖性分析。通过将它们与我们策划的手动注释数据集进行比较以及通过单独评估的手动注释数据集进行了比较，可以评估生成的开关点的质量。我们发现，我们的方法论产生的点的大约96％在DJ混合物中具有良好的质量。
The automatic identification of cue points is a central task in applications as diverse as music thumbnailing, mash-ups generation, and DJ mixing. Our focus lies in electronic dance music and in specific cue points, the "switch points", that make it possible to automatically construct transitions among tracks, mimicking what professional DJs do. We present an approach for the detection of switch points that embody a few general rules we established from interviews with professional DJs; the implementation of these rules is based on features extraction and novelty analysis. The quality of the generated switch points is assessed both by comparing them with a manually annotated dataset that we curated, and by evaluating them individually. We found that about 96\% of the points generated by our methodology are of good quality for use in a DJ mix.
