Introducing a Dataset of Guitar Sounds for Electric Guitars Model Recognition

Profeta R, Schuller G. Introducing a Dataset of Guitar Sounds for Electric Guitars Model Recognition. In: AES Convention 144. Audio Engineering Society; 2018. Paper 436. Available from: https://aes.org/publications/elibrary-page/?id=19549

@inproceedings{Profeta2018_19549,
  author = {Profeta, Renato and Schuller, Gerald},
  title = {{Introducing a Dataset of Guitar Sounds for Electric Guitars Model Recognition}},
  booktitle = {AES Convention 144},
  note = {Paper 436},
  year = {2018},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19549}
}

TY  - CPAPER
TI  - Introducing a Dataset of Guitar Sounds for Electric Guitars Model Recognition
AU  - Profeta, Renato
AU  - Schuller, Gerald
T2  - AES Convention 144
M1  - Paper 436
PY  - 2018
DA  - 2018/05/06
UR  - https://aes.org/publications/elibrary-page/?id=19549
PB  - Audio Engineering Society
LA  - en
AB  - This engineering brief introduces a dataset of electric guitar sounds. The main goal of the dataset is to provide a set of electric guitar recordings that can be used for research in identification and/or classification of different electric guitar types. The dataset, at its current stage, consists of recordings from 30 guitars of different manufacturers and types, with around 3500 music events. All audio files are acquired in one-channel, 16-bit waveform audio file format with a sampling rate of 44100 Hz and are accompanied by parameter annotations in xml format. The dataset is planned to include recordings of over 50 guitars and will be released in uncompressed wav file format under Creative Commons License.
ER  -