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.
Weitere Kapitel dieses Buchs durch Wischen aufrufen
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
- Analysis of the Utility of Classical and Novel Speech Quality Measures for Speaker Verification
- Springer Berlin Heidelberg
Neuer Inhalt/© ITandMEDIA