Multiple Phase Information Combination for Replay Attacks Detection

Dongbo Li, Longbiao Wang, Jianwu Dang, Meng Liu, Zeyan Oo, Seiichi Nakagawa, Haotian Guan, Xiangang Li

In recent years, the performance of Automatic Speaker Verification (ASV) systems has been improved significantly. However, they are still affected by different kind of spoofing attacks. In this paper, we propose a method that fused different phase features and amplitude features to detect replay attacks. We propose the mel-scale relative phase feature and apply source-filter vocal tract feature in phase domain for replay attacks detection. These two phase-based features are combined to get complementary information. In addition to these phase haracteristics, constant Q cepstral coefficients (CQCCs) are used. The proposed methods are evaluated using the ASVspoof 2017 challenge database and Gaussian mixture model was used as the back-end model. The proposed approach achieved 55.6% relative error reduction rate than the conventional magnitude-based feature.

 DOI: 10.21437/Interspeech.2018-2001

Cite as: Li, D., Wang, L., Dang, J., Liu, M., Oo, Z., Nakagawa, S., Guan, H., Li, X. (2018) Multiple Phase Information Combination for Replay Attacks Detection. Proc. Interspeech 2018, 656-660, DOI: 10.21437/Interspeech.2018-2001.

  author={Dongbo Li and Longbiao Wang and Jianwu Dang and Meng Liu and Zeyan Oo and Seiichi Nakagawa and Haotian Guan and Xiangang Li},
  title={Multiple Phase Information Combination for Replay Attacks Detection},
  booktitle={Proc. Interspeech 2018},