#18 Automatic Detection of Multiple, Cascaded Audio Effects in Guitar Recordings
This paper presents a method to detect and distinguish single and multiple audio effects in monophonic electric guitar recordings. It is based on spectral analysis of audio segments located in the sustain part of 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. A novel database that consists of approx. 50000 guitar tones was assembled for the purpose of evaluation. Classification accuracy reached 99.2% for the detection and distinction of arbitrary combinations of six frequently used audio effects.