EGFxSet (Electric Guitar Effects dataset) features recordings for all clean tones in a 22-fret Stratocaster, recorded with 5 different pickup configurations, also processed through 12 popular guitar effects. Our dataset was recorded in real hardware, making it relevant for music information retrieval tasks on real music. We also include annotations for parameter settings of the effects we used.

EGFxSet is a dataset of 8,970 audio files with a 5-second duration each, summing a total time of 12 hours and 28 minutes.

All possible 138 notes of a standard tuning 22 frets guitar were recorded in each one of the 5 pickup configurations, giving a total of 690 clean tone audio files ( 58 min ).

The 690 clean audio (58 min) files were processed through 12 different audio effects employing actual guitar gear (no VST emulations were used), summing a total of 8,280 processed audio files (11 hours 30 min).

The effects employed were divided into four categories, and each category comprised three different effects. Some gear used supported the generation of more than one effect setting (but only one was recorded at a time).

Categories, Models and Effects: Distortion (Blues Driver, Tube Screamer, RAT2 Distortion), Modulation (Chorus, Phaser, Flanger), Delays (Digital Delay, Tape Echo, Sweep Echo), Reverb (Plate Reverb, Hall Reverb, Spring Reverb).

Annotations are labeled by a trained electric guitar musician. For each tone, we provide: Guitar string number, Fret number, Guitar pickup configuration, Effect name, Effect type, Hardware modes, Knob names, Knob types, Knob settings).

The dataset website is: https://egfxset.github.io/

The data can be accessed here: https://zenodo.org/record/7044411#.YxKdSWzMKEI

An ISMIR extended abstract was presented in 2022: https://ismir2022.ismir.net/program/lbd/

This dataset was conceived during Iran Roman's "Deep Learning for Music Information Retrieval" course imparted in the postgraduate studies in music technology at the UNAM (Universidad Nacional Autónoma de México). The result is a combined effort between two UNAM postgraduate students (Hegel Pedroza and Gerardo Meza) and Iran Roman (NYU).