Table 1.

(A) classification accuracy for AD/CN and AD stages/CN models after applying acoustic features and data augmentation methods. (B) Model evaluation metrics for Random Forest classifier before and after applying data augmentation methods for Task 1. (C) Random Forest classier accuracy before and after applying data augmentation methods for Task 2.

Model	Accuracy (%) (Task 1)	Accuracy (%) (Task 2)
(1A)
SVM	78.6	65.2
Logistic Regression	66.2	56.7
Random Forest	82.2	71.5
(B)
Random Forest Classifier	Task 1 (Before applying data augmentation methods)	Task 1 (After applying data augmentation methods)
Accuracy (%)	72.6	82.2
AUC (%)	75.7	89.3
Recall (%)	73.4	81.4
Precision (%)	74.9	81.6
(C)
Random Forest Classifier	Task 2 (Before applying data augmentation methods)	Task 2 (After applying data augmentation methods)
Accuracy (%)	46.3	71.5