Automatic Detection of Audio Effects in Guitar and Bass Recordings

Stein M, Abeßer J, Dittmar C, Schuller G. Automatic Detection of Audio Effects in Guitar and Bass Recordings. In: AES Convention 128. Audio Engineering Society; 2010. Paper 8013. Available from: https://aes.org/publications/elibrary-page/?id=15310

@inproceedings{Stein2010_15310,
  author = {Stein, Michael and Abeßer, Jakob and Dittmar, Christian and Schuller, Gerald},
  title = {{Automatic Detection of Audio Effects in Guitar and Bass Recordings}},
  booktitle = {AES Convention 128},
  note = {Paper 8013},
  year = {2010},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15310}
}

TY  - CPAPER
TI  - Automatic Detection of Audio Effects in Guitar and Bass Recordings
AU  - Stein, Michael
AU  - Abeßer, Jakob
AU  - Dittmar, Christian
AU  - Schuller, Gerald
T2  - AES Convention 128
M1  - Paper 8013
PY  - 2010
DA  - 2010/05/06
UR  - https://aes.org/publications/elibrary-page/?id=15310
PB  - Audio Engineering Society
LA  - en
AB  - This paper presents a novel method to detect and distinguish ten frequently used audio effects in recordings of electric guitar and bass. It is based on spectral analysis of audio segments located in the sustain part of previously detected guitar tones. Overall, 541 spectral, cepstral and harmonic features are extracted from short time spectra of the audio segments. Support Vector Machines are used in combination with feature selection and transform techniques for automatic classification based on the extracted feature vectors. With correct classification rates up to 100% for the detection of single effects and 98% for the simultaneous distinction of ten different effects, the method has successfully proven its capability - performing on isolated sounds as well as on multitimbral, stereophonic musical recordings.
ER  -