Artificial Intelligence Review

, Volume 27, Issue 4, pp 295–307

An evaluation of one-class classification techniques for speaker verification

  • Anthony Brew
  • Marco Grimaldi
  • Pádraig Cunningham


Speaker verification is a challenging problem in speaker recognition where the objective is to determine whether a segment of speech in fact comes from a specific individual. In supervised machine learning terms this is a challenging problem as, while examples belonging to the target class are easy to gather, the set of counter-examples is completely open. This makes it difficult to cast this as a supervised classification problem as it is difficult to construct a representative set of counter examples. So we cast this as a one-class classification problem and evaluate a variety of state-of-the-art one-class classification techniques on a benchmark speech recognition dataset. We construct this as a two-level classification process whereby, at the lower level, speech segments of 20 ms in length are classified and then a decision on an complete speech sample is made by aggregating these component classifications. We show that of the one-class classification techniques we evaluate, Gaussian Mixture Models shows the best performance on this task.


One-class classifiers Speaker verification Gaussian mixture models 


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  1. Bimbot F, Bonastre J, Fredouille C, Gravier G, Magrin-Chagnolleau I, Meignier S, Merlin T, Ortega-Garcia J, Petrovska-Delacretaz, Reynolds D D (2004) A tutorial on text-independent speaker verification. EURASIP J Appl Signal Process 4: 430–451CrossRefGoogle Scholar
  2. Bradley AP (1997) The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit 30(7): 1145–1159CrossRefGoogle Scholar
  3. Cummins F, Grimaldi M, Leonard T, Simko J (2006) The CHAINS corpus: CHAracterizing INdividual Speakers. In: Proceedings of SPECOM’06, pp 431–435Google Scholar
  4. Kittler J, Hatef M, Duin RPW, Matas J (1998) On combining classifiers. Pattern Anal Mach Intell IEEE Trans 20(3): 226–239CrossRefGoogle Scholar
  5. Reynolds D (1995) Speaker identification and verification using Gaussian mixture speaker models. Speech Commun 17(1): 91–108CrossRefGoogle Scholar
  6. Reynolds D (2002) An overview of automatic speaker recognition technology. In: Proceedings of the International Conference on Acoustics, Speech, and Signal ProcessingGoogle Scholar
  7. Reynolds DA (2003) Channel robust speaker verification via feature mapping. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP ’03), vol 2, pp II–53–6Google Scholar
  8. Reynolds DA, Rose RC (1995) Robust text-independent speaker identification using gaussian mixture speaker models. Speech Audio Process IEEE Trans 3(1): 72–83CrossRefGoogle Scholar
  9. Reynolds DA, Quatieri TF, Dunn RB (2000) Speaker verification using adapted gaussian mixture models. Digital Signal Processing, pp 19–41Google Scholar
  10. Taniguchi M, Tresp V (1997) Averaging regularized estimators. Neural Comput 9(5): 1163–1178CrossRefGoogle Scholar
  11. Tax DMJ (2001) One-class classification. Ph.D. thesis, Delft University of TechnologyGoogle Scholar
  12. Tax DMJ, Duin RPW (1999) Support vector domain description. Pattern Recogn Lett 20(11–13): 1191–1199CrossRefGoogle Scholar
  13. Tax DMJ, Muller KR (2004) A consistency-based model selection for one-class classification. In: Proceedings of the 17th International Conference on Pattern Recognition (ICPR 2004), vol 3, pp 363–366Google Scholar
  14. Wan V, Renals S (2005) Speaker verification using sequence discriminant support vector machines. Speech Audio Process IEEE Trans 13(2): 203–210CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Anthony Brew
    • 1
  • Marco Grimaldi
    • 1
  • Pádraig Cunningham
    • 1
  1. 1.Department of Computer Science and InformaticsUniversity College DublinDublinIreland

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