Article ID Journal Published Year Pages File Type
4973688 Computer Speech & Language 2017 20 Pages PDF
Abstract
Recent evaluations such as ASVspoof 2015 and the similarly-named AVspoof have stimulated a great deal of progress to develop spoofing countermeasures for automatic speaker verification. This paper reports an approach which combines speech signal analysis using the constant Q transform with traditional cepstral processing. The resulting constant Q cepstral coefficients (CQCCs) were introduced recently and have proven to be an effective spoofing countermeasure. An extension of previous work, the paper reports an assessment of CQCCs generalisation across three different databases and shows that they deliver state-of-the-art performance in each case. The benefit of CQCC features stems from a variable spectro-temporal resolution which, while being fundamentally different to that used by most automatic speaker verification system front-ends, also captures reliably the tell-tale signs of manipulation artefacts which are indicative of spoofing attacks. The second contribution relates to a cross-database evaluation. Results show that CQCC configuration is sensitive to the general form of spoofing attack and use case scenario. This finding suggests that the past single-system pursuit of generalised spoofing detection may need rethinking.
Related Topics
Physical Sciences and Engineering Computer Science Signal Processing
Authors
, , ,