Impostor Detection in Speaker Recognition Using Confusion-Based Confidence Measures

  • Kim, Kyu-Hong (School of Engineering, ICU and is currently with the Computing Technology Lab., Samsung Advanced Institute of Technology) ;
  • Kim, Hoi-Rin (School of Engineering, ICU) ;
  • Hahn, Min-Soo (School of Engineering, ICU)
  • Received : 2005.11.23
  • Published : 2006.12.31

Abstract

In this letter, we introduce confusion-based confidence measures for detecting an impostor in speaker recognition, which does not require an alternative hypothesis. Most traditional speaker verification methods are based on a hypothesis test, and their performance depends on the robustness of an alternative hypothesis. Compared with the conventional Gaussian mixture model-universal background model (GMM-UBM) scheme, our confusion-based measures show better performance in noise-corrupted speech. The additional computational requirements for our methods are negligible when used to detect or reject impostors.

Keywords