Computer and Modernization ›› 2013, Vol. 1 ›› Issue (4): 5-9.doi: 10.3969/j.issn.1006-2475.2013.04.002

• 人工智能 • Previous Articles     Next Articles

Research on Method of Speaker Verification Based on Support Vector Data Description Model

CHEN Jue-zhi1, ZHANG Gui-rong2, ZHOU Yu-huan3   

  1. 1. Department of Information, Naval Command Academy, Nanjing 211800, China;2. Metering Station, Troop 92601 of PLA, Zhanjiang 524009, China;3. Institute of Command Information System, PLA University of Science and Technology, Nanjing 210007, China
  • Received:2013-03-12 Revised:1900-01-01 Online:2013-04-17 Published:2013-04-17

Abstract: With the purpose of improving the performance of speaker verification, a novel speaker verification method based on support vector data description (SVDD) model is proposed. The traditional hard decision method of SVDD is changed to a novel soft decision method based on the sample acceptance rate, therefore the confidence scores are normalized to the value [0,1] so as to simplify the threshold value setting. Simulation experiments show that the performance of speaker verification based on this novel method is remarkably better than that based on Gaussian mixture model (GMM) customarily.

Key words: speaker recognition, speaker verification, support vector data description (SVDD), Gaussian mixture model (GMM)

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