Abstract
Speaker verification (ASV) systems are still vulnerable to different kinds of spoofing attacks, especially replay attack due to high-quality playback devices. Many countermeasures have been developed recently. Most of the efforts focus on the search for more salient features and many new features have been proposed. Five kinds of features, namely Mel-frequency cepstral coefficients (MFCCs), linear frequency cepstral coefficients (LFCCs), inverted Mel-frequency cepstral coefficients (IMFCCs), constant Q cepstral coefficients (CQCCs) and bottleneck features were compared on the public ASVspoof 2017 and BTAS 2016 datasets in this paper. Our experimental results show that MFCCs and bottleneck features yield comparable results. Both of them significantly outperform others (including the recently proposed CQCCs). However, the number of filters and cepstral bins are essential to the success of MFCCs.
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