GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Poly Discrete)

<strong>GUITAR-FX-DIST</strong> is a dataset of electric guitar recordings processed with overdrive, distortion and fuzz audio effects. It was developed for research in guitar effects detection, classification and parameters estimation. The dataset is also useful for research on automatic music transcription, intelligent music production, signal processing or effects modelling. It contains both unprocessed and processed recordings. The dataset is split into 4 sub-datasets: Mono Continuous, Mono Discrete, Poly Continuous, Poly Discrete <strong>Authors:</strong> Marco Comunità - Centre for Digital Music, Queen Mary University of London <strong>Reference:</strong> If you make use of GUITAR-FX-DIST, please cite the following publication: <pre><code>@article{comunità2021guitar, title={Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks}, author={Comunità, Marco and Stowell, Dan and Reiss, Joshua D.}, journal={Journal of the Audio Engineering Society}, year={2021}, volume={69}, number={7/8}, pages={594-604}, doi={}, month={July} }</code></pre> <strong>Dataset Snapshot:</strong> <strong>Size:</strong> ~550k samples (~305 hours) + 550k mel spectrograms <strong>Audio Format:</strong> WAV - 44.1kHz, 16bit, mono, -6dBFS <strong>Mel-Spectrogram Format:</strong> NPY - 128 frequency bands, sample rate 22050Hz, window length 1024, hop size 512, <strong>Effects:</strong> 14 between overdrive, distortion and fuzz <strong>Unprocessed recordings</strong> 624 monophonic notes 420 polyphonic (2, 3 and 4 notes intervals and chords) 2 guitars, with up to 2 pick-up settings and up to 3 plucking styles (finger pluck - hard, finger pluck - soft, pick) Schecter Diamond C-1 Classic Chester Stratocaster <strong>Samples length:</strong> 2 sec <strong>Unprocessed Recordings:</strong> The original (unprocessed) recordings are from the IDMT-SMT-Audio-Effects dataset. For details please refer to the website and the accompagning publication: <em>Stein, Michael; Abeßer, Jakob; Dittmar, Christian; Schuller, Gerald: Automatic Detection of Audio Effects in Guitar and Bass Recordings. Proceedings of the AES 128th Convention, 2010.</em> <strong>Processed Recordings:</strong> The processed recordings are divided into 4 sub-datasets which are named depending on the unprocessed recordings used (monophonic or polyphonic) and on the settings' values (discrete or continuous). The sub-datasets are called: Mono Discrete, Poly Discrete, Mono Continuous, Poly Continuous Mono Discrete and Poly Discrete use a discrete set of combinations selected as the most common and representative settings a person might use (see README file for details). For Mono Continuous and Poly Continuous both unprocessed samples as well as settings’ values are drawn from a uniform distribution (10000 samples for each effect). Samples: Mono Discrete: ~160k Poly Discrete: ~110k Mono Continuous: 140k Poly Continuous: 140k <strong>Scripts:</strong> The dataset includes the MATLAB scripts used to generate the samples**GUITAR-FX-DIST** 数据集是一批经过过载、失真与法兹音频效果处理的电吉他录音数据集。该数据集由伦敦玛丽女王大学数字音乐中心的Marco Comunità开发，专为吉他效果检测、分类及参数估计相关研究打造，同时也可应用于自动音乐转录、智能音乐制作、信号处理或效果建模等领域的研究。本数据集包含未处理与已处理两类录音，并被划分为4个子数据集：单音连续（Mono Continuous）、单音离散（Mono Discrete）、复音连续（Poly Continuous）与复音离散（Poly Discrete）。 **作者：** Marco Comunità — 伦敦玛丽女王大学数字音乐中心 **引用说明：** 若您使用GUITAR-FX-DIST数据集，请引用以下文献： @article{comunità2021guitar, title={Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks}, author={Comunità, Marco and Stowell, Dan and Reiss, Joshua D.}, journal={Journal of the Audio Engineering Society}, year={2021}, volume={69}, number={7/8}, pages={594-604}, doi={}, month={July} } **数据集概览：** **数据规模：** 约55万个样本（约305小时）+ 55万个梅尔频谱图 **音频格式：** 波形音频（WAV）格式，采样率44.1kHz，位深度16bit，单声道，电平为-6dBFS **梅尔频谱图（Mel-Spectrogram）格式：** NumPy数组（NPY）格式，包含128个频带，采样率22050Hz，窗长1024，跳步长度512 **效果类型：** 涵盖过载、失真与法兹三类共14种效果组合 **未处理录音：** 包含624个单音音符与420个复音音符（涵盖2、3、4音符构成的音程与和弦），采用2款吉他，支持最多2种拾音器配置与3种拨奏风格（强力手指拨奏、轻柔手指拨奏、拨片拨奏），吉他型号为Schecter Diamond C-1 Classic与Chester Stratocaster。 **单样本时长：** 2秒 **原始未处理录音来源：** 本数据集的原始未处理录音取自IDMT-SMT-Audio-Effects数据集，详细信息请参阅其官方网站及配套文献：*Stein, Michael; Abeßer, Jakob; Dittmar, Christian; Schuller, Gerald: Automatic Detection of Audio Effects in Guitar and Bass Recordings. Proceedings of the AES 128th Convention, 2010.* **已处理录音：** 已处理录音根据所用未处理录音的类型（单音或复音）以及参数设置的类型（离散或连续）划分为4个子数据集，分别为：单音离散（Mono Discrete）、复音离散（Poly Discrete）、单音连续（Mono Continuous）与复音连续（Poly Continuous）。其中单音离散与复音离散数据集选用了最常用且具代表性的参数组合集合（详细说明请参阅README文件）；单音连续与复音连续数据集的未处理样本及参数设置值均取自均匀分布（每种效果对应10000个样本）。 各子数据集规模如下： - 单音离散（Mono Discrete）：约16万个样本 - 复音离散（Poly Discrete）：约11万个样本 - 单音连续（Mono Continuous）：14万个样本 - 复音连续（Poly Continuous）：14万个样本 **配套脚本：** 本数据集包含用于生成样本的MATLAB脚本。