A new feature for automatic speaker verification anti-spoofing: Constant Q cepstral coefficients

Todisco, Massimiliano; Delgado, Hector; Evans, Nicholas
ODYSSEY 2016, The Speaker and Language Recognition Workshop, June 21-24, 2016, Bilbao, Spain

Best Paper Award

Efforts to develop new countermeasures in order to protect automatic speaker verification from spoofing have intensified over recent years. The ASVspoof 2015 initiative showed that there is great potential to detect spoofing attacks, but also that the detection of previously unforeseen spoofing attacks remains challenging. This paper argues that there is more to be gained from the study of features rather than classifiers and introduces a new feature for spoofing detection based on the constant Q transform, a perceptually-inspired time-frequency analysis tool popular in the study of music. Experimental results obtained using the standard ASVspoof 2015 database show that, when coupled with a standard Gaussian mixture model-based classifier, the proposed constant Q cepstral coefficients (CQCCs) outperform all previously reported results by a significant margin. In particular, those for a subset of unknown spoofing attacks (for which no matched training data was used) is 0.46%, a relative improvement of 72% over the best, previously reported results. 


DOI
Type:
Conference
City:
Bilbao
Date:
2016-06-21
Department:
Digital Security
Eurecom Ref:
4855
Copyright:
© ISCA. Personal use of this material is permitted. The definitive version of this paper was published in ODYSSEY 2016, The Speaker and Language Recognition Workshop, June 21-24, 2016, Bilbao, Spain and is available at : http://dx.doi.org/10.21437/Odyssey.2016-41

PERMALINK : https://www.eurecom.fr/publication/4855