Freesound Loop Dataset

<strong>Freesound Loop Dataset</strong> This dataset contains 9,455 loops from Freesound.org and the corresponding annotations. These loops have tempo, key, genre and instrumentation annotation. <strong>Dataset Construction</strong> To collect this dataset, the following steps were performed: Freesound was queried with "loop" and "bpm", so as to collect loops which have a beats-per-minute(BPM) annotations. The sounds were analysed with AudioCommons extractor, so as to obtain key information. The textual metadata of each sound was analysed, to obtain the BPM proposed by the user, and to obtain genre information. Annotators used a web interface to annotate around 3,000 loops. <strong>Dataset Organisation</strong> The dataset contains two folders and two files in the root directory: 'FSL10K' encloses the audio files and their metadata and analysis. The audios are in the 'audio' folder and are named '&lt;freesound_sound_id&gt;.wav'. The AudioCommons analysis of the loops is present in the 'ac_analysis' directory, while the Essentia analysis of the loops obtained through the Freesound API is on the 'fs_analysis' directory. The textual metadata for each audio can be found in the 'metadata.json'. Finally, the audio analysis provided by the algorithms which were benchmarked in the paper is on the 'benchmark' directory. 'annotations' holds the expert provided annotation for the sounds in the dataset. The annotations are separated in a folder for each annotator and each annotation is stored as a .json file, named 'sound-&lt;freesound_sound_id&gt;.json', with a key for each of the features extracted. <strong>Licenses</strong> All the sounds have some kind of Creative Commons license. The license of each sound in the dataset can be obtained from the 'FSL10K/metadata.json' file <strong>Authors and Contact</strong> This dataset was developed by António Ramires et. al. Any questions related to this dataset please contact: António Ramires [e-mail] [e-mail] <strong>References</strong> Please cite this paper if you use this dataset: <code>@inproceedings{ramires2020, author = "Antonio Ramires and Frederic Font and Dmitry Bogdanov and Jordan B. L. Smith and Yi-Hsuan Yang and Joann Ching and Bo-Yu Chen and Yueh-Kao Wu and Hsu Wei-Han and Xavier Serra", title = "The Freesound Loop Dataset and Annotation Tool", booktitle = "Proc. of the 21st International Society for Music Information Retrieval (ISMIR)", year = "2020" } </code> <strong>Acknowledgements</strong> This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 765068 (MIP-Frontiers).

<strong>Freesound循环数据集（Freesound Loop Dataset）</strong> 本数据集收录了来自Freesound.org的9455个循环音频片段及其对应标注信息，所有片段均包含速度、调式、音乐流派与乐器配置相关标注。
<strong>数据集构建</strong>：本数据集的采集流程如下：以"loop"与"bpm"为关键词检索Freesound平台，收集带有每分钟节拍数（beats-per-minute, BPM）标注的循环音频片段。随后使用AudioCommons提取工具对音频进行分析，以获取调式相关信息；同时解析每条音频的文本元数据，提取用户提交的BPM值与音乐流派信息。另有约3000个循环片段由标注人员通过网页界面完成人工标注。
<strong>数据集组织结构</strong>：根目录下包含2个文件夹与2个文件：'FSL10K'文件夹存放音频文件及其元数据与分析结果，其中音频文件位于子文件夹'audio'内，命名格式为「<freesound_sound_id>.wav」。AudioCommons对循环片段的分析结果存放于'ac_analysis'目录；通过Freesound API获取的Essentia分析结果则存储于'fs_analysis'目录。每条音频的文本元数据可在'metadata.json'文件中查询。此外，论文基准测试所用算法生成的音频分析结果存放于'benchmark'目录。'annotations'文件夹存储专家对数据集内音频的人工标注结果：标注按标注人员划分为不同子文件夹，每份标注以「sound-<freesound_sound_id>.json」为文件名存储，文件内以键值对形式存储各提取特征的信息。
<strong>授权协议</strong>：所有音频片段均采用知识共享（Creative Commons）类授权协议，单条音频的授权协议可通过'FSL10K/metadata.json'文件查询。
<strong>作者与联系方式</strong>：本数据集由António Ramires等人开发。若有相关疑问，请联系：António Ramires，邮箱：[e-mail]、[e-mail]。
<strong>引用方式</strong>：若使用本数据集，请引用以下论文：
<code>@inproceedings{ramires2020, author = "Antonio Ramires and Frederic Font and Dmitry Bogdanov and Jordan B. L. Smith and Yi-Hsuan Yang and Joann Ching and Bo-Yu Chen and Yueh-Kao Wu and Hsu Wei-Han and Xavier Serra", title = "The Freesound Loop Dataset and Annotation Tool", booktitle = "Proc. of the 21st International Society for Music Information Retrieval (ISMIR)", year = "2020" }</code>
<strong>致谢</strong>：本研究获得欧盟地平线2020研究与创新计划资助，项目编号为Marie Skłodowska-Curie协议第765068号（MIP-Frontiers）。