Abnormal Voice Detection Algorithm Based on Semi-Supervised Co-Training Algorithm
Ya Hui Zhao, Hong Li Wang, Rong Yi Cui · Advanced materials research · 2012
The AR-Tri-training algorithm is proposed for applying to the abnormal voice detection, and voice detection software is designed by mixed programming used Matlab and VC in this paper. Firstly, training samples are collected and the features of each sample are extracted including centroid, spectral entropy, wavelet and MFCC. Secondly, the assistant learning strategy is proposed, AR-Tri-training algorithm is designed by combining the rich information strategy. Finally, Classifiers are trained by using AR-Tri-training algorithm, and the integrated classifier is applied to voice detection. As can be drawn from the experimental results, AR-Tri-training not only removes mislabeled examples in training process, but also takes full advantage of the unlabeled examples and wrong-learning examples on validation set