Analysis of the Utility of Classical and Novel Speech Quality Measures for Speaker Verification

  • Alberto Harriero
  • Daniel Ramos
  • Joaquin Gonzalez-Rodriguez
  • Julian Fierrez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)


In this work, we analyze several quality measures for speaker verification from the point of view of their utility, i.e., their ability to predict performance in an authentication task. We select several quality measures derived from classic indicators of speech degradation, namely ITU P.563 estimator of subjective quality, signal to noise ratio and kurtosis of linear predictive coefficients. Moreover, we propose a novel quality measure derived from what we have called Universal Background Model Likelihood (UBML), which indicates the degradation of a speech utterance in terms of its divergence with respect to a given universal model. Utility of quality measures is evaluated following the protocols and databases of NIST Speaker Recognition Evaluation (SRE) 2006 and 2008 (telephone-only subset), and ultimately by means of error-vs.-rejection plots as recommended by NIST. Results presented in this study show significant utility for all the quality measures analyzed, and also a moderate decorrelation among them.


Speaker verification quality utility SNR degradation indicator 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Alberto Harriero
    • 1
  • Daniel Ramos
    • 1
  • Joaquin Gonzalez-Rodriguez
    • 1
  • Julian Fierrez
    • 1
  1. 1.ATVS – Biometric Recognition Group, Escuela Politecnica SuperiorUniversidad Autonoma de MadridMadridSpain

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