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Artefacts that differentiate spoofed from bona-fide utterances can reside in spectral or temporal domains.
“Asvspoof 2015: the first automatic speaker verification spoofing and countermeasures challenge,”
Z. Wu, T. Kinnunen, N. Evans et al., · 2015
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S. Ioffe and C. Szegedy, · 2015
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D. P. Kingma and J. Ba, · 2015
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“Investigation of sub-band discriminative information between spoofed and genuine speech.,”
K. Sriskandaraja, V. Sethu, P. N. Le and E. Ambikairajah, · 2016
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“Identity mappings in deep residual networks,”
K. He, X. Zhang, S. Ren and J. Sun, · 2016
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“The asvspoof 2017 challenge: Assessing the limits of replay spoofing attack detection,”
T. Kinnunen, M. Sahidullah, H. Delgado et al., · 2017
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“Self-normalizing neural networks,”
G. Klambauer, T. Unterthiner, A. Mayr and S. Hochreiter, · 2017
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“Audio replay attack detection with deep learning frameworks,”
G. Lavrentyeva, S. Novoselov, E. Malykh et al., · 2017
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“Population based training of neural networks,”
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“Graph attention networks,”
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“A light cnn for deep face representation with noisy labels,”
X. Wu, R. He, Z. Sun and T. Tan, · 2018
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“t-dcf: a detection cost function for the tandem assessment of spoofing countermeasures and automatic speaker verification,”
T. Kinnunen, K. A. Lee, H. Delgado et al., · 2018
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“Speaker recognition from raw waveform with sincnet,”
M. Ravanelli and Y. Bengio, · 2018
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“Asvspoof 2019: Future horizons in spoofed and fake audio detection,”
M. Todisco, X. Wang, V. Vestman et al., · 2019
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“Significance of subband features for synthetic speech detection,”
J. Yang, R. K. Das and H. Li, · 2019
Cited alongside, same era.
“Replay attack detection with complementary high-resolution information using end-to-end dnn for the asvspoof 2019 challenge,”
J. Jung, H. Shim, H. Heo and H. Yu, · 2019
Cited alongside, same era.
“Heterogeneous graph attention network,”
X. Wang, H. Ji, C. Shi et al., · 2019
Cited alongside, same era.
“Bert: Pre-training of deep bidirectional transformers for language understanding,”
J. D. M.-W. C. Kenton and L. K. Toutanova, · 2019
Cited alongside, same era.
“Self-attention graph pooling,”
J. Lee, I. Lee and J. Kang, · 2019
Cited alongside, same era.
“Graph u-nets,”
H. Gao and S. Ji, · 2019
Cited alongside, same era.
“End-to-end spectro-temporal graph attention networks for speaker verification anti-spoofing and speech deepfake detection,”
H. Tak, J. Jung, J. Patino et al., · 2021
Closest in time.
“End-to-end anti-spoofing with rawnet2,”
H. Tak, J. Patino, M. Todisco et al., · 2021
Closest in time.
“Graph attention networks for speaker verification,”
J. Jung, H. Heo, H. Yu and J. S. Chung, · 2021
Closest in time.
“The effect of silence and dual-band fusion in anti-spoofing system,”
Y. Zhang, W. Wang and P. Zhang, · 2021
Closest in time.
“Towards end-to-end synthetic speech detection,”
G. Hua, A. Beng jin teoh and H. Zhang, · 2021
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“Raw differentiable architecture search for speech deepfake and spoofing detection,”
W. Ge, J. Patino, M. Todisco and N. Evans, · 2021
Closest in time.
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“An explainability study of the constant Q cepstral coefficient spoofing countermeasure for automatic speaker verification,”
H. Tak, J. Patino, A. Nautsch et al., · 2020
Cited alongside, same era.
“Spoofing Attack Detection using the Non-linear Fusion of Sub-band Classifiers,”
H. Tak, J. Patino, A. Nautsch et al., · 2020
Cited alongside, same era.
“Improved RawNet with Feature Map Scaling for Text-Independent Speaker Verification Using Raw Waveforms,”
J. Jung, S. Kim, H. Shim et al., · 2020
Cited alongside, same era.
“Integrated replay spoofing-aware text-independent speaker verification,”
H. Shim, J. Jung, J. Kim and H. Yu, · 2020
Cited alongside, same era.
“Generalization of audio deepfake detection,”
T. Chen, A. Kumar, P. Nagarsheth et al., · 2020
Cited alongside, same era.
“Asvspoof 2019: A large-scale public database of synthesized, converted and replayed speech,”
X. Wang, J. Yamagishi, M. Todisco et al., · 2020
Cited alongside, same era.
“Channel-wise gated res2net: Towards robust detection of synthetic speech attacks,”
X. Li, X. Wu, H. Lu et al., · 2021
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“A Comparative Study on Recent Neural Spoofing Countermeasures for Synthetic Speech Detection,”
X. Wang and J. Yamagishi, · 2021
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“A capsule network based approach for detection of audio spoofing attacks,”
A. Luo, E. Li, Y. Liu et al., · 2021
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“One-class learning towards synthetic voice spoofing detection,”
Y. Zhang, F. Jiang and Z. Duan, · 2021
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“Replay and synthetic speech detection with res2net architecture,”
X. Li, N. Li, C. Weng et al., · 2021
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“Improved lightcnn with attention modules for asv spoofing detection,”
X. Ma, T. Liang, S. Zhang et al., · 2021
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“Partially-Connected Differentiable Architecture Search for Deepfake and Spoofing Detection,”
W. Ge, M. Panariello, J. Patino et al., · 2021
Closest in time.