期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：1
页码：109-120
DOI：10.14257/ijsip.2014.7.1.11
出版社：SERSC
摘要：Speaker Recognition is a challenging task and is widely used in many speech aided applications. This study proposes a new Neural Network (NN) model for identifying the speaker, based on the acoustic features of a given speech sample extracted by applying wavelet transform on raw signals. Wrapper based feature selection applies dimensionality reduction by kernel PCA and ranking by Info gain. Only top ranked features are selected and used for neural network classifier. The proposed neural network classifier is trained to assign a speaker name as label to the test voice data. Multi-Layer Perceptron (MLP) is implemented for classification, and the performance is compared with the proposed NN model.
