Playing technique classification for bowed string instruments from raw audio

Abstract

Music instrument playing technique classification based on raw audio is a relatively unexplored area of music information retrieval research. This study systematically investigates the use of traditional audio features augmented by features based on the Hartley transform, used as input to a multiclass support vector machine (SVM) classifier, to identify up to 11 different playing techniques performed on each of the violin, viola, cello, and contrabass. Furthermore, 36- and 44-class joint instrument and playing technique classifiers were developed that achieved macro-average F-measures exceeding 0.88. Our approach expands and improves on the state-of-the-art study, which implemented sparse-coded magnitude and phase-derived spectral features.