A Study on GMM Optimization with Clustering for Improving Speaker Recognition
Lin Jiang-yun · Computer Technology and Development · 2009
Gaussian mixture model(GMM) has been widely used for text-independent speaker recognition.This method has simple and efficient character.However,if it has a large number of Gaussians in GMM,it leads to a large complexity of computation.To solve this problem,proposes a new method which combines classical GMM with clustering algorithm to optimize the GMM for reducing the complexity of computation.Experimental results demonstrated that our approach was quite efficient to reduce the complexity of computation.