BIOSIG 2017, 16th International Conference of the Biometrics Special Interest Group, September 20-22, 2017, Darmstadt, Germany
Vulnerabilities to presentation attacks can undermine confidence in automatic speaker verification (ASV) technology. While efforts to develop countermeasures, known as
presentation attack detection (PAD) systems, are now under way, the majority of past work has been performed with high-quality speech data. Many practical ASV applications are narrowband and encompass various coding and other channel effects. PAD
performance is largely untested in such scenarios. This paper reports an assessment of the impact of bandwidth and channel variation on PAD performance. Assessments using two current PAD solutions and two standard databases show that they provoke significant degradations in performance. Encouragingly, relative performance improvements of 98% can nonetheless be achieved through feature optimisation. This performance gain is
achieved by optimising the spectro-temporal decomposition in the feature extraction process to compensate for narrowband speech. However, compensating for channel variation is considerably more challenging.
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