The week's pick
Reseach Article
Hierarchical Speaker Identification based on Latent Variable Decomposition
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 19 - Number 7 |
| Year of Publication: 2011 |
| Authors: Sabyasachi Patra, Subhendu Kumar Acharya |
10.5120/2376-3131
|
Sabyasachi Patra, Subhendu Kumar Acharya . Hierarchical Speaker Identification based on Latent Variable Decomposition. International Journal of Computer Applications. 19, 7 ( April 2011), 6-11. DOI=10.5120/2376-3131
Abstract
In this paper, a novel hierarchical speaker identification method based on Latent Variable Decomposition (LVD) has been proposed. Firstly, we got a coarse decision by a fast scan all registered speakers using LVD based features and GMM classifier to find R possible target speakers, and then MFCC or PCA based features were used to make final decision. LVD has another advantage: reduction of the feature vectors dimensions, and the noise is removed from speech simultaneity. So, it can reduce the computational complexity and improve the performance of speaker identification. The experimental results showed that the proposed method could improve recognition accuracy of system remarkably and the system has better robustness by comparing with the traditional speaker identification method.
References
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