ToneTwist AFx Dataset: Harley Benton Silly Fuzz

Settings

Volume
Fuzz

10
1

10
5

10
10

Dry with markers

Dry inputs are a selection of clean guitar and bass recordings from different sources:

IDMT-SMT-GUITAR - dataset 2 (7:23 min)

IDMT-SMT-GUITAR - dataset 4 - Career SG (6:08 min)

IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820 (5:14 min)

IDMT-SMT-Bass-Single-Track - (5:58 min)

NAM: Neural Amp Modeler - (3:11 min)

Private Guitar Data - (5:19 min)

YouTube Bass Recordings - (10:09 min)

Pre-processing:

All:

synchronization markers (2 impulses) added at start and end of every file

IDMT-SMT-GUITAR - dataset 2:

peak normalized to -6dBFS

NAM:

no pre-processing

Others:

peak normalized to -0.1dBFS

signal multiplied by random number every 5 seconds (uniform distribution [0.1, 1.0] = [-20dB, 0dB])

Authors

Marco Comunità - Centre for Digital Music, Queen Mary University of London

Github

https://github.com/mcomunita/tonetwist-afx-dataset

Reference

If you make use of AUDIO-EFFECTS-DATASET, please cite the following publication:

@misc{comunità2025nablafxframeworkdifferentiableblackbox,
title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects},
author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
year={2025},
eprint={2502.11668},
archivePrefix={arXiv},
primaryClass={cs.SD},
url={https://arxiv.org/abs/2502.11668},
}

数据集设置

参数列表
音量（Volume） 法兹失真参数（Fuzz）
10 1
10 5
10 10

带同步标记的干信号

干信号为多源精选的纯净吉他与贝斯录音，具体来源如下：
- IDMT-SMT-GUITAR - dataset 2：时长7分23秒
- IDMT-SMT-GUITAR - dataset 4 - Career SG：时长6分08秒
- IDMT-SMT-GUITAR - dataset 4 - Ibanez 2820：时长5分14秒
- IDMT-SMT-Bass-Single-Track：时长5分58秒
- 神经网络放大器建模器（Neural Amp Modeler，NAM）：时长3分11秒
- Private Guitar Data：时长5分19秒
- YouTube Bass Recordings：时长10分09秒

预处理流程

通用处理：
所有音频文件均在文件首尾添加2个脉冲作为同步标记

IDMT-SMT-GUITAR - dataset 2专属处理：
将峰值归一化至-6分贝满刻度（decibels relative to full scale，dBFS）

神经网络放大器建模器（NAM）专属处理：
无预处理流程

其余数据集专属处理：
将峰值归一化至-0.1分贝满刻度，并每5秒将信号乘以一个服从[0.1, 1.0]（对应[-20dB, 0dB]）均匀分布的随机数

作者
马可·科穆尼塔（Marco Comunità）——伦敦大学玛丽女王学院数字音乐中心

GitHub仓库
https://github.com/mcomunita/tonetwist-afx-dataset

参考文献
若您使用本音频效果数据集（AUDIO-EFFECTS-DATASET），请引用以下文献：
@misc{comunità2025nablafxframeworkdifferentiableblackbox,
title={NablAFx: A Framework for Differentiable Black-box and Gray-box Modeling of Audio Effects},
author={Marco Comunità and Christian J. Steinmetz and Joshua D. Reiss},
year={2025},
eprint={2502.11668},
archivePrefix={arXiv},
primaryClass={cs.SD},
url={https://arxiv.org/abs/2502.11668},
}