We present the open-source implementation of the first fully automatic and comprehensive DJ system, able to generate seamless music mixes using songs from a given library much like a human DJ does.The proposed system is built on top of several enhanced music information retrieval (MIR) techniques, such as for beat tracking, downbeat tracking, and structural segmentation, to obtain an understanding of the musical structure. Leveraging the understanding of the music tracks offered by these state-of-the-art MIR techniques, the proposed system surpasses existing automatic DJ systems both in accuracy and completeness. To the best of our knowledge, it is the first fully integrated solution that takes all basic DJing best practices into account, from beat and downbeat matching to identification of suitable cue points, determining a suitable cross-fade profile and compiling an interesting playlist that trades off innovation with continuity.To make this possible, we focused on one specific sub-genre of electronic dance music, namely Drum and Bass. This allowed us to exploit genre-specific properties, resulting in a more robust performance and tailored mixing behavior.Evaluation on a corpus of 160 Drum and Bass songs and an additional hold-out set of 220 songs shows that the used MIR algorithms can annotate 91% of the songs with fully correct annotations (tempo, beats, downbeats, and structure for cue points). On these songs, the proposed song selection process and the implemented DJing techniques enable the system to generate mixes of high quality, as confirmed by a subjective user test in which 18 Drum and Bass fans participated.

中文翻译：

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从原始音频到无缝混音：为 Drum 和 Bass 创建自动 DJ 系统

我们展示了第一个全自动和综合 DJ 系统的开源实现，能够像人类 DJ 一样使用给定库中的歌曲生成无缝的音乐混音。提议的系统建立在几个增强的音乐信息检索之上（ MIR) 技术，例如节拍跟踪、强拍跟踪和结构分割，以获得对音乐结构的理解。利用对这些最先进的 MIR 技术提供的音乐曲目的理解，所提出的系统在准确性和完整性方面都超越了现有的自动 DJ 系统。据我们所知，它是第一个完全集成的解决方案，它考虑了所有基本的 DJ 最佳实践，从节拍和强拍匹配到识别合适的提示点，确定合适的交叉淡入淡出配置文件并编译一个有趣的播放列表，在创新与连续性之间进行权衡。为了实现这一点，我们专注于电子舞曲的一个特定子类型，即鼓和贝斯。这使我们能够利用特定流派的属性，从而产生更强大的性能和量身定制的混合行为。 对 160 首鼓和贝斯歌曲以及一组额外的 220 首歌曲的评估表明，所使用的 MIR 算法可以注释 91带有完全正确注释（节奏、节拍、强拍和提示点结构）的歌曲百分比。在这些歌曲上，提议的歌曲选择过程和实施的 DJ 技术使系统能够生成高质量的混音，这一点得到了 18 名鼓和贝斯迷参与的主观用户测试的证实。