Stein, Michael; Abeßer, Jakob; Dittmar, Christian; Schuller,Gerald:

Automatic Detection of Audio Effects in Guitar and Bass Recordings. Proceedings of the AES 128th Convention, 2010.

Database content

The IDMT-SMT-Audio-Effects database is a large database for automatic detection of audio effects in recordings of electric guitar and bass and related signal processing.

The overall duration of the audio material is approx. 30 hours.

The dataset consists of 55044 WAV files (44.1 kHz, 16bit, mono) with single recorded notes:

  • 20592 monophonic bass notes
  • 20592 monophonic guitar notes
  • 13860 polyphonic guitar sounds

Overall, 11 different audio effects are incorporated:

  • feedback delay
  • slapback delay
  • reverb
  • chorus
  • flanger
  • phaser
  • tremolo
  • vibrato
  • distortion
  • overdrive
  • no effect (unprocessed notes/sounds)

2 different electric guitars and 2 different electric bass guitars, each with two different pick-up settings and up to three different plucking styles (finger plucked - hard, finger plucked - soft, picked) were used for recording.

The notes cover the common pitch range of a 4-string bass guitar from E1 (41.2 Hz) to G3 (196.0 Hz) or the common pitch range of a 6-string electric guitar from E2 (82.4 Hz) to E5 (659.3 Hz).

Effects processing was performed using a digital audio workstation and a variety of mostly freely available effect plugins.

To organize the database, lists in XML format are used, which record all relevant information and are provided with the database as well as a summary of the used effect plugins and parameter settings.

In addition, most of this information is also encoded in the first part of the file name of the audio files using a simple alpha-numeric encoding scheme. The second part of the file name contains unique identification numbers. This provides an option for fast and flexible structuring of the data for various purposes.


This work has been partly supported by the German research project GlobalMusic2One funded by the Federal Ministry of Education and Research (BMBF-FKZ: 01/S08039B). Additionally, the Thuringian Ministry of Economy, Employment and Technology supported this research by granting funds of the European Fund for Regional development to the project Songs2See, enabling transnational cooperation between Thuringian companies and their partners from other European regions.

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