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This paper reports the first successful application of a differentiable architecture search (DARTS) approach to the deepfake and spoofing detection problems.
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M. Todisco, H. Delgado, and N. Evans, “A New Feature for Automatic Speaker Verification Anti-Spoofing: Constant Q Cepstral Coefficients,” in Proc. Speaker Odyssey 2016 , vol. 2016, 2016, pp. 283–290
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G. Valenti, H. Delgado, M. Todisco, N. W. Evans, and L. Pilati, “An end-to-end spoofing countermeasure for automatic speaker verification using evolving recurrent neural networks,” in Proc. Speaker Odyssey 2018 , 2018, pp. 288–295
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T. Kinnunen, K. A. Lee, H. Delgado, N. Evans, M. Todisco, M. Sahidullah, J. Yamagishi, and D. Reynolds, “t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification,” in Proc. Speaker Odyssey 2018 , 2018
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M. Sahidullah, H. Delgado, M. Todisco, T. Kinnunen, N. Evans, J. Yamagishi, and K. Lee, “Introduction to voice presentation attack detection and recent advances,” in Handbook of Biometric Anti-Spoofing - Presentation Attack Detection, Second Edition , ser. Advances in Computer Vision and Pattern Recognition. Springer, 2019, pp. 321–361
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R. Li, M. Zhao, Z. Li, L. Li, and Q. Hong, “Anti-Spoofing Speaker Verification System with Multi-Feature Integration and Multi-Task Learning,” in Proc. Interspeech 2019 , 2019, pp. 1048–1052
2019
Cited alongside, same era.
Cheng-I Lai and Nanxin Chen and Jesús Villalba and Najim Dehak, “ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual Networks,” in Proc. Interspeech 2019 , 2019, pp. 1013–1017
2019
Cited alongside, same era.
J.-w. Jung, H.-S. Heo, J.-h. Kim, H.-j. Shim, and H.-J. Yu, “RawNet: Advanced End-to-End Deep Neural Network Using Raw Waveforms for Text-Independent Speaker Verification,” Proc. Interspeech 2019 , pp. 1268–1272, 2019
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T. Elsken, J. H. Metzen, F. Hutter et al. , “Neural architecture search: A survey.” Machine Learnign Research , vol. 20, no. 55, pp. 1–21, 2019
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Yi-Chen Chen and Jui-Yang Hsu and Cheng-Kuang Lee and Hung-yi Lee, “DARTS-ASR: Differentiable Architecture Search for Multilingual Speech Recognition and Adaptation,” in Proc. Interspeech 2020 , 2020, pp. 1803–1807
2020
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S. Ding, T. Chen, X. Gong, W. Zha, and Z. Wang, “AutoSpeech: Neural Architecture Search for Speaker Recognition,” in Proc. Interspeech 2020 , 2020, pp. 916–920
2020
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X. Wang, J. Yamagishi, M. Todisco, H. Delgado, A. Nautsch, N. Evans, M. Sahidullah, V. Vestman, T. Kinnunen, K. A. Lee et al. , “ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech,” Computer Speech & Language , vol. 64, p. 101114, 2020
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H. Liu, K. Simonyan, and Y. Yang, “DARTS: Differentiable Architecture Search,” in Proc. ICML 2019 , 2019
2019
Cited alongside, same era.
2019
Cited alongside, same era.
M. Todisco, X. Wang, V. Vestman, M. Sahidullah, H. Delgado, A. Nautsch et al. , “ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection,” in Proc. Interspeech 2019 , 2019, pp. 1008–1012
2019
Cited alongside, same era.
G. Lavrentyeva, S. Novoselov, A. Tseren, M. Volkova, A. Gorlanov, and A. Kozlov, “STC Antispoofing Systems for the ASVspoof2019 Challenge,” pp. 1033–1037, 2019
2019
Cited alongside, same era.
S. Liu, H. Wu, H.-y. Lee, and H. Meng, “Adversarial attacks on spoofing countermeasures of automatic speaker verification,” in Proc. IEEE ASRU 2019 . IEEE, 2019, pp. 312–319
2019
Cited alongside, same era.
M. Alzantot, Z. Wang, and M. B. Srivastava, “Deep Residual Neural Networks for Audio Spoofing Detection,” Proc. Interspeech 2019 , pp. 1078–1082, 2019
2019
Cited alongside, same era.
H. Tak, J. Patino, M. Todisco, A. Nautsch, N. Evans, and A. Larcher, “End-to-end anti-spoofing with RawNet2,” Proc. ICASSP 2020 (to appear) , 2020
2020
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T. Chen, A. Kumar, P. Nagarsheth, G. Sivaraman, and E. Khoury, “Generalization of audio deepfake detection,” in Proc. Speaker Odyssey 2020 , 2020, pp. 1–5
2020
Later among the works it cites.
Z. Yu, C. Zhao, Z. Wang, Y. Qin, Z. Su, X. Li, F. Zhou, and G. Zhao, “Searching Central Difference Convolutional Networks for Face Anti-Spoofing,” pp. 5294–5304, 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
A. Daniel, “Evolving Recurrent Neural Networks That Process and Classify Raw Audio in a Streaming Fashion,” in Proc. Interspeech 2017 , 2017, pp. 2040–2041
2041
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