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The IIR Submission to CSLP 2006 Speaker Recognition Evaluation

  • Kong-Aik Lee
  • Hanwu Sun
  • Rong Tong
  • Bin Ma
  • Minghui Dong
  • Changhuai You
  • Donglai Zhu
  • Chin-Wei Eugene Koh
  • Lei Wang
  • Tomi Kinnunen
  • Eng-Siong Chng
  • Haizhou Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4274)

Abstract

This paper describes the design and implementation of a practical automatic speaker recognition system for the CSLP speaker recognition evaluation (SRE). The speaker recognition system is built upon four subsystems using speaker information from acoustic spectral features. In addition to the conventional spectral features, a novel temporal discrete cosine transform (TDCT) feature is introduced in order to capture long-term speech dynamic. The speaker information is modeled using two complementary speaker modeling techniques, namely, Gaussian mixture model (GMM) and support vector machine (SVM). The resulting subsystems are then integrated at the score level through a multilayer perceptron (MLP) neural network. Evaluation results confirm that the feature selection, classifier design, and fusion strategy are successful, giving rise to an effective speaker recognition system.

Keywords

Discrete Cosine Transform Speaker Recognition Speaker Verification Voice Activity Detector Test Segment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kong-Aik Lee
    • 1
  • Hanwu Sun
    • 1
  • Rong Tong
    • 1
  • Bin Ma
    • 1
  • Minghui Dong
    • 1
  • Changhuai You
    • 1
  • Donglai Zhu
    • 1
  • Chin-Wei Eugene Koh
    • 2
  • Lei Wang
    • 2
  • Tomi Kinnunen
    • 1
  • Eng-Siong Chng
    • 2
  • Haizhou Li
    • 1
    • 2
  1. 1.Institute for Infocomm ResearchSingapore
  2. 2.School of Computer EngineeringNanyang Technological UniversitySingapore

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