Table 13.

K-fold cross-validation results with MFCC, CQT features using machine learning models.

Features	DT	SVC	KNN	LR	NB	RF	Voting (Hard)	Voting (Soft)
MFCC	0.93(± 0.08)	0.99 (± 0.02)	0.85 (± 0.08)	0.96 (± 0.05)	0.99 (± 0.02)	0.98 (± 0.02)	-	-
CQT	0.92(± 0.05)	0.94 (± 0.04)	0.80 (± 0.10)	0.90 (± 0.05)	0.72 (± 0.15)	0.95 (± 0.07)	0.94 (± 0.04)	0.94 (± 0.04)
MFCC+CQT	0.91(± 0.07)	0.95 (± 0.05)	0.83 (± 0.07)	0.90 (± 0.04)	0.48 (± 0.09)	0.95 (± 0.04)	0.94 (± 0.04)	0.90 (± 0.05)