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Journal of Electrical and Computer Engineering
Volume 2017, Article ID 1735698, 9 pages
https://doi.org/10.1155/2017/1735698
Research Article

Speaker Recognition Using Wavelet Packet Entropy, I-Vector, and Cosine Distance Scoring

Laboratory of Cyberspace, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China

Correspondence should be addressed to She Kun; nc.ude.ctseu@nuk

Received 16 February 2017; Revised 17 April 2017; Accepted 26 April 2017; Published 14 May 2017

Academic Editor: Lei Zhang

Copyright © 2017 Lei Lei and She Kun. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Today, more and more people have benefited from the speaker recognition. However, the accuracy of speaker recognition often drops off rapidly because of the low-quality speech and noise. This paper proposed a new speaker recognition model based on wavelet packet entropy (WPE), i-vector, and cosine distance scoring (CDS). In the proposed model, WPE transforms the speeches into short-term spectrum feature vectors (short vectors) and resists the noise. I-vector is generated from those short vectors and characterizes speech to improve the recognition accuracy. CDS fast compares with the difference between two i-vectors to give out the recognition result. The proposed model is evaluated by TIMIT speech database. The results of the experiments show that the proposed model can obtain good performance in clear and noisy environment and be insensitive to the low-quality speech, but the time cost of the model is high. To reduce the time cost, the parallel computation is used.