Usefulness of linear prediction residual for replay attack detection

Abstract

This work demonstrates the usefulness of processing linear prediction (LP) residual signal for detecting replay attacks. The playback device having non-flat frequency response modulates the input signal passing through it, resulting spectral distortion in replay signals especially in the low frequency regions (0–300 Hz). In effect, the excitation source information present below 300 Hz gets distorted. The linear prediction (LP) residual signal implicitly contains excitation source information. The excitation source feature, residual mel frequency cepstral coefficients (RMFCC) obtained from the LP residual signal has been proposed for replay detection task. The significance of RMFCC feature has been investigated through Gaussian mixtures model-universal background model (GMM-UBM) ASV experiments and spoof detection experiments using self-developed IITG-MV replay database and standard ASVspoof 2017 database, respectively. For IITG-MV, relative tandem-detection cost function (t-DCF) improvements of 29.78% (male), 7.96% (female) and 24.52% (whole-set) are observed for RMFCC+MFCC combination over MFCC feature. For ASVspoof 2017, relative EER improvements of 37.34% are reported for RMFCC+CQCC combination over CQCC feature. Minimum reported EER is 9.50% for RMFCC+CQCC system. Experimental results shows that the RMFCC feature contains information complementary to MFCC and CQCC features.