Table 1.

Classification accuracy of several shallow machine learning models.

Feature/classifier	NB	KNN	LogitReg	RF	SGD	XGB	SVM
Chroma	0.51 ± 0.01	0.54 ± 0.03	0.55 ± 0.03	0.55 ± 0.03	0.52 ± 0.03	0.53 ± 0.03	0.54 ± 0.03
MelSpectrum	0.54 ± 0.03	0.65 ± 0.03	0.63 ± 0.03	0.63 ± 0.03	0.56 ± 0.03	0.63 ± 0.03	0.63 ± 0.04
MFCC	0.55 ± 0.04	0.65 ± 0.04	0.62 ± 0.04	0.64 ± 0.02	0.57 ± 0.04	0.63 ± 0.03	0.62 ± 0.03
PowerSpec	0.54 ± 0.03	0.64 ± 0.04	0.62 ± 0.03	0.63 ± 0.02	0.57 ± 0.04	0.62 ± 0.03	0.64 ± 0.02
RAW	0.53 ± 0.02	0.59 ± 0.03	0.59 ± 0.03	0.58 ± 0.03	0.54 ± 0.03	0.58 ± 0.03	0.59 ± 0.04
Spec	0.57 ± 0.05	0.65 ± 0.03	0.66 ± 0.03	0.67 ± 0.04	0.58 ± 0.04	0.66 ± 0.02	0.65 ± 0.02
Tonal	0.52 ± 0.02	0.54 ± 0.02	0.55 ± 0.04	0.54 ± 0.03	0.52 ± 0.03	0.53 ± 0.03	0.54 ± 0.02