Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration. It is a creative and time-consuming task commonly performed by an expert music engineer. In this paper, we propose a method for automatically rearranging music recordings that takes into account the hierarchical structure of the recording. Previous approaches focus solely on identifying cut-points in the audio that could result in smooth transitions. We instead utilize deep audio representations to hierarchically segment the piece and define a cut-point search subject to the boundaries and musical functions of the segments. We score suitable entry- and exit-point pairs based on their similarity and the segments they belong to, and define an optimal path search. Experimental results demonstrate the selected cut-points are most commonly imperceptible by listeners and result in more consistent musical development with less distracting repetitions.

翻译：音乐重编排涉及对音乐作品中的片段进行重排、删除和重复，旨在生成具有不同时长的独立版本。这是一项创意性强且耗时的工作，通常由专业音乐工程师完成。本文提出了一种自动重编排音乐录音的方法，该方法充分考虑了录音的层级结构。以往的研究仅侧重于识别音频中可能实现平滑过渡的切分点。我们则利用深度音频表示对音乐作品进行层级分割，并基于片段的边界及其音乐功能定义切分点搜索范围。根据候选入口-出口点对的相似性及其所属片段进行评分，并定义最优路径搜索。实验结果表明，所选切分点最不易被听众察觉，且能实现更连贯的音乐发展，减少令人分心的重复。