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

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

Introduced by Marco Comunità et al. in Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks6 Dec 2020 archive 2025-07-28

GUITAR-FX-DIST 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

Authors:

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

Reference:

If you make use of GUITAR-FX-DIST, please cite the following publication:

@article{comunita2020guitar,
  title={Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks},
  author={Comunit{\`a}, Marco and Stowell, Dan and Reiss, Joshua D},
  journal={arXiv preprint arXiv:2012.03216},
  year={2020}
}

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

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License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

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Variants archive 2025-07-28

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

1 variant name, as the archive lists them.

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