GiantSteps+ EDM Key Dataset

The GiantSteps+ EDM Key Dataset includes 600 two-minute sound excerpts from various EDM subgenres, annotated with single-key labels. This dataset focus in problematic Beatport excerpts, so it is biased, but it is interesting to test the robustness of key recognition systems. These 600 tracks have been analysed by Daniel G. Camhi and Ángel Faraldo, providing pitch-class set descriptions, key and modal changes, comments and confidence levels for the individual tracks. This dataset is a revision of the original GiantSteps Key Dataset, available in Github (<https://github.com/GiantSteps/giantsteps-key-dataset>) and initially described in: Knees, P., Faraldo, Á., Herrera, P., Vogl, R., Böck, S., Hörschläger, F., Le Goff, M. (2015). Two Datasets for Tempo Estimation and Key Detection in Electronic Dance Music Annotated from User Corrections. In Proceedings of the 16th International Society for Music Information Retrieval Conference, 364–370. Málaga, Spain. The original audio samples belong to online audio snippets from Beatport, an online music store for DJ's and Electronic Dance Music Producers (<http:\\www.beatport.com>). If this dataset were used in further research, we would appreciate the citation of the current DOI (10.5281/zenodo.1101082) and the following doctoral dissertation, where a detailed description of the properties of this dataset can be found: Ángel Faraldo (2017). Tonality Estimation in Electronic Dance Music: A Computational and Musically Informed Examination. PhD Thesis. Universitat Pompeu Fabra, Barcelona.

GiantSteps+ EDM关键数据集（GiantSteps+ EDM Key Dataset）包含来自各类电子舞曲（Electronic Dance Music，简称EDM）子流派的600段时长为2分钟的音频片段，均标注有单调式标签。该数据集聚焦于存在标注问题的Beatport平台音频片段，因此存在一定偏倚，但非常适合用于测试调式识别系统的鲁棒性。

该600首曲目由Daniel G. Camhi与Ángel Faraldo完成分析，为每首曲目提供了音级集合（pitch-class set）描述、调与调式变化信息、标注注释以及置信度等级。

本数据集是原始GiantSteps关键数据集（GiantSteps Key Dataset）的修订版本，原始数据集可在GitHub（<https://github.com/GiantSteps/giantsteps-key-dataset>）获取，其初始学术描述出自如下文献：Knees, P., Faraldo, Á., Herrera, P., Vogl, R., Böck, S., Hörschläger, F., Le Goff, M. (2015). 《基于用户校正标注的电子舞曲节奏估计与调式检测双数据集》，收录于《第16届国际音乐信息检索学会会议论文集》，第364-370页，西班牙马拉加。

原始音频样本均取自Beatport平台的在线音频片段——该平台是面向DJ与电子舞曲制作人的在线音乐商店（<http://www.beatport.com>）。

若将本数据集用于后续研究，请引用当前的DOI（10.5281/zenodo.1101082）以及如下博士学位论文，该论文中详细阐述了本数据集的各项属性：Ángel Faraldo (2017). 《电子舞曲的调式估计：基于计算与音乐学视角的考察》，博士学位论文，庞培法布拉大学，巴塞罗那。