WHAT?

EGFxSet contains recordings of all clean tones in a Stratocaster guitar, with augmentations by processing the audios through twelve electric guitar effects. Similar datasets apply effects using software, EGFxSet in contrast uses real guitar effects hardware, making it relevant to develop MIR tools with applications on real music. Annotations include all guitar and effect parameters controlled during our dataset recording. EGFxSet contains 8970 unique, annotated guitar tones, and is published with full open-access rights.

HOW?

All possible notes of an standard tuning electric guitar were recorded using the instrument input of an Audient iD14 audio interface. Using the interface output, the recordings of each sound effect were processed for recording using the line input of the same interface. Both, the previously recorded clean guitar sounds and the processed recordings were normalized.

All the sounds of the dataset were annotated by a professional guitarist. Each file’s annotations are:

• String-Fret tuple: digits indicating the string number (1 through 6) and fret number (0 for open strings, and 1 through 22 for fret position).


• Note: the guitar had standard tuning, so the note played can be inferred with string-fret tuple.


• Pickup configuration: one of the five possible pickup configurations: bridge, bridge-middle, middle, middle-neck, or neck.


• Effect: this is the name of the effect used (i.e. blues driver, chorus, or plate reverb).


• Model: this is the commercial name and version of the ef120 fect hardware used.


• Effect type: a categorical name for the effect type, abstracting away the effect’s specific name and brand.


• Knob names: each effect we used has controllable parameters with names given by the original manufacturer.


• Knob type: we use language descriptors from our functional categorization of effect controls to categorize each effect’s controllable parameters.


• Setting: a value (between 0.0 and 1.0, or bpm for rate effects, or name of selected category) indicating the setting captured.

WHY?

Existing datasets use software emulations of analog gear to apply effects on clean guitar recordings, and few include effect parameter annotations. As a result, there is a need for datasets featuring recordings of clean electric guitar tones, augmented using real effects hardware, and including annotations of effects and guitar settings.