Replay attack detection with auditory filter-based relative phase features

@article{Oo2019ReplayAD,
  title={Replay attack detection with auditory filter-based relative phase features},
  author={Zeyan Oo and Longbiao Wang and Khomdet Phapatanaburi and Meng Liu and Seiichi Nakagawa and Masahiro Iwahashi and Jianwu Dang},
  journal={EURASIP Journal on Audio, Speech, and Music Processing},
  year={2019},
  volume={2019},
  pages={1-11}
}
There are many studies on detecting human speech from artificially generated speech and automatic speaker verification (ASV) that aim to detect and identify whether the given speech belongs to a given speaker. Recent studies demonstrate the success of the relative phase (RP) feature in speaker recognition/verification and the detection of synthesized speech and converted speech. However, there are few studies that focus on the RP feature for replay attack detection. In this paper, we improve… Expand
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References

SHOWING 1-10 OF 48 REFERENCES
Detecting Converted Speech and Natural Speech for anti-Spoofing Attack in Speaker Recognition
TLDR
Experiments show that the performance of the features derived from phase spectrum outperform the melfrequency cepstral coefficients (MFCCs) tremendously: even without converted speech for training, the equal error rate (EER) is reduced from 20.20% of MFCCs to 2.35%. Expand
Spoofing Speech Detection Using Modified Relative Phase Information
TLDR
Modified relative phase (MRP) information extracted from a Fourier spectrum is proposed for spoofing speech detection and it significantly outperforms the MFCC, modified group delay, and other phase information based features. Expand
Relative phase information for detecting human speech and spoofed speech
TLDR
In this study, relative phase information extracted from a Fourier spectrum is used to detect human and spoofed speech and significantly outperforms the MFCC and modified group delay. Expand
Novel Variable Length Teager Energy Separation Based Instantaneous Frequency Features for Replay Detection
TLDR
A novel replay detector based on Variable length Teager Energy OperatorEnergy Separation Algorithm-Instantaneous Frequency Cosine Coefficients (VESA-IFCC) for the ASV spoof 2017 challenge is proposed and the performance of the proposed feature set is compared with the features developed for detecting synthetic and voice converted speech. Expand
Multiple Phase Information Combination for Replay Attacks Detection
TLDR
This paper applies the mel-scale relative phase feature and source-filter vocal tract feature in phase domain for replay attacks detection and achieves 55.6% relative error reduction rate than the conventional magnitude-based feature. Expand
DNN-Based Amplitude and Phase Feature Enhancement for Noise Robust Speaker Identification
TLDR
Simultaneous enhancement of amplitude and phase based feature was effective, and it achieved about 24% relative error reduction comparing with individual feature enhancement. Expand
Spoofing detection goes noisy: An analysis of synthetic speech detection in the presence of additive noise
TLDR
A significant gap is revealed between the performance of state-of-the-art spoofing detectors between clean and noisy conditions and a study with two score fusion strategies shows that combining different feature based systems improves recognition accuracy for known and unknown attacks in both clean and noise conditions. Expand
Auditory Filterbank Learning for Temporal Modulation Features in Replay Spoof Speech Detection
TLDR
A standalone replay spoof speech detection system to classify the natural vs. replay speech signals using Convolutional Restricted Boltzmann Machine (ConvRBM) with the pre-emphasized speech signals. Expand
Spoof Detection Using Source, Instantaneous Frequency and Cepstral Features
TLDR
The main focus of this work is on exploiting the differences in the speech-specific nature of genuine speech signals and spoofed speech signals generated by replay attacks. Expand
Exploration of Compressed ILPR Features for Replay Attack Detection
TLDR
This work explores the use of discrete cosine transform compressed integrated linear prediction residual (ILPR) features for discriminating between genuine and replayed signals in the problem of detecting replay attacks on speaker verification systems. Expand
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