Usefulness of linear prediction residual signal for development of replay attacks detection system

Abstract

Spoofing automatic speaker verification systems by using pre-recorded speech samples is called as replay attack. The availability of high quality recording and replay devices (i.e. smart phones) has made replay attacks more easily accessible, even with minimal or no specific speech processing knowledge. This work demonstrates the usefulness of linear prediction (LP) residual signal for the development of replay attacks detection system. The level of discriminatory information available in LP residual signal is investigated and compared with recently proposed playback detection algorithm (PAD), that relies on the information present in speech signal spectrograms. We observed that LP residual spectra are comparatively distinguishable. A comparative study for speech and LP residual signals is performed by speaker verification experiments under replay attacks. Results show that information present in LP residual is relatively more robust and effective in reducing the false acceptance rate. We conclude, LP residual signals may equally be useful for the development of replay attacks detection system.