Table 4.

Results of machine learning classifiers using MFCC features.

Model	Class	Precision	Recall	F1 Score	Model	Class	Precision	Recall	F1 Score
DT	0	0.96	0.92	0.94	LR	0	1.0	0.92	0.96
	1	1.00	1.00	1.00		1	1.00	1.00	1.00
	2	0.92	0.96	0.94		2	0.92	1.0	0.96
	Micro avg.	0.96	0.96	0.96		Micro avg.	0.97	0.97	0.97
	Weighted avg.	0.96	0.96	0.96		Weighted avg.	0.97	0.97	0.97
	Accuracy	0.96				Accuracy	0.97
SVC	0	0.98	0.98	0.98	NB	0	0.63	0.81	0.71
	1	1.00	1.00	1.00		1	1.00	1.00	1.00
	2	0.98	0.98	0.98		2	0.74	0.53	0.62
	Micro avg.	0.99	0.99	0.99		Micro avg.	0.79	0.78	0.78
	Weighted avg.	0.99	0.99	0.99		Weighted avg.	0.79	0.78	0.77
	Accuracy	0.99				Accuracy	0.78
KNN	0	0.78	0.79	0.78	RF	0	0.96	0.94	0.95
	1	1.00	1.00	1.00		1	1.00	1.00	1.00
	2	0.79	0.78	0.78		2	0.94	0.96	0.95
	Micro avg.	0.86	0.86	0.86		Micro avg.	0.97	0.97	0.97
	Weighted avg.	0.85	0.85	0.85		Weighted avg.	0.97	0.97	0.97
	Accuracy	0.85				Accuracy	0.97
HardVoting	0	0.98	0.96	0.97	Soft Voting	0	0.98	0.96	0.97
	1	1.00	1.00	1.00		1	1.00	1.00	1.00
	2	0.96	0.98	0.97		2	0.96	0.98	0.97
	Micro avg.	0.98	0.98	0.98		Micro avg.	0.98	0.98	0.98
	Weighted avg.	0.98	0.98	0.98		Weighted avg.	0.98	0.98	0.98
	Accuracy	0.98				Accuracy	0.98