Journal of Applied Sciences ›› 2014, Vol. 32 ›› Issue (6): 582-587.doi: 10.3969/j.issn.0255-8297.2014.06.006

• Signal and Information Processing • Previous Articles     Next Articles

Automatic Speaker Recognition for Courtroom Based on Adaptive Within-Source-Variance Control

WANG Hua-peng1,2, YANG Jun1, WU Ming1, XU Yong1   

  1. 1. Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences,
    Beijing 100190, China
    2. Department of Forensic Science and Technology, China Criminal Police University,
    Shenyang 110854, China
  • Received:2012-07-24 Revised:2014-09-10 Online:2014-11-28 Published:2014-09-10

Abstract:  This paper proposes a method to transfer the scores generated from a speaker recognition system to
likelihood ratios (LR) for evaluating the strength of forensic voice evidence. A robust LR estimation algorithm
using adaptive within-source-variance control is developed to accurately estimate a model of the suspect. The
algorithm adaptively combines information of reference speakers and that of the suspect to model the withinsource-
variability of the suspect. Compared with a baseline recognition system, the system using the proposed
algorithm has better discrimination capability and reliability, and the magnitude of evidence strength is also
improved.  

Key words:  forensic automatic speaker recognition, background-model-Gaussian mixture model (BM-GMM), likelihood ratio, adaptive within-source variance control