The setlist identification (SLI) task addresses a music recognition use case where the goal is to retrieve the metadata and timestamps for all the tracks played in live music events. Due to various musical and non-musical changes in live performances, developing automatic SLI systems is still a challenging task that, despite its industrial relevance, has been under-explored in the academic literature. In this paper, we propose an end-to-end workflow that identifies relevant metadata and timestamps of live music performances using a version identification system. We compare 3 of such systems to investigate their suitability for this particular task. For developing and evaluating SLI systems, we also contribute a new dataset that contains 99.5h of concerts with annotated metadata and timestamps, along with the corresponding reference set. The dataset is categorized by audio qualities and genres to analyze the performance of SLI systems in different use cases. Our approach can identify 68% of the annotated segments, with values ranging from 35% to 77% based on the genre. Finally, we evaluate our approach against a database of 56.8k songs to illustrate the effect of expanding the reference set, where we can still identify 56% of the annotated segments.

中文翻译：

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研究音乐版本检索系统对清单识别的功效

设置列表标识（SLI）任务解决了一种音乐识别用例，其中的目标是检索现场音乐事件中播放的所有曲目的元数据和时间戳。由于现场表演中各种音乐和非音乐的变化，开发自动SLI系统仍然是一项具有挑战性的任务，尽管具有工业意义，但在学术文献中却未对此进行深入研究。在本文中，我们提出了一种端到端工作流，该工作流使用版本识别系统识别相关的元数据和现场音乐表演的时间戳。我们比较了3个这样的系统，以研究它们是否适合此特定任务。为了开发和评估SLI系统，我们还贡献了一个新数据集，其中包含带有注释的元数据和时间戳的99.5h音乐会以及相应的参考集。该数据集按音频质量和流派分类，以分析SLI系统在不同用例中的性能。我们的方法可以识别68％的带注释片段，基于类型，其值的范围从35％到77％。最后，我们针对56.8万首歌曲的数据库评估了我们的方法，以说明扩展参考集的效果，在该参考集中，我们仍然可以识别出56％的带注释段。