Fetching the paper…
Reading the bibliography…
Automatic Speaker Verification systems are gaining popularity these days; spoofing attacks are of prime concern as they make these systems vulnerable.
S.J. Pan, and Q. Yang, 2010. ”A survey on transfer learning,” in
2010
Earlier work this paper cites.
B.C. Moore, ”An introduction to the psychology of hearing,” Brill, 2012
2012
Earlier work this paper cites.
A. Van den Oord, S. Dieleman, and B. Schrauwen, “Deep content-based music recommendation,” in
2013
Earlier work this paper cites.
S. Dieleman, and B. Schrauwen, “End-to-end learning for music audio,” in
2014
Earlier work this paper cites.
J. Schlüter, and S. Bock, “Improved musical onset detection with convolutional neural networks,” in
2014
Earlier work this paper cites.
K. Ullrich, J. Schlüter, and T. Grill, “Boundary detection in music structure analysis using convolutional neural networks,” in
2014
Earlier work this paper cites.
K. Simonyan and A. Zisserman, ”Very deep convolutional networks for large-scale image recognition,”
2014
Cited alongside, same era.
Z. Wu, N. Evans, T. Kinnunen, J. Yamagishi, F. Alegre, and H. Li, ”Spoofing and countermeasures for speaker verification: A survey,” in
2015
Cited alongside, same era.
Z. Wu, T. Kinnunen, N. Evans, J. Yamagishi, C. Hanilçi, M. Sahidullah, and A. Sizov, ”ASVspoof 2015: the first automatic speaker verification spoofing and countermeasures challenge,” in
2015
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, ”Deep residual learning for image recognition,” in
2016
Cited alongside, same era.
K. Choi, G. Fazekas, and M. Sandler, “Automatic tagging using deep convolutional neural networks,” in
2016
Cited alongside, same era.
T. Kinnunen, M. Sahidullah, H. Delgado, M. Todisco, N. Evans, J. Yamagishi, and K.A. Lee, ”The ASVspoof 2017 challenge: Assessing the limits of replay spoofing attack detection,” 2017
2017
Later among the works it cites.
G. Lavrentyeva, S. Novoselov, E. Malykh, A. Kozlov, O. Kudashev, and V. Shchemelinin, ”Audio Replay Attack Detection with Deep Learning Frameworks,” in
2017
Later among the works it cites.
H.A. Patil, H.A. Kamble, T.B. Patel, and M.H. Soni, ”Novel Variable Length Teager Energy Separation Based Instantaneous Frequency Features for Replay Detection,” in
2017
Later among the works it cites.
K.R. Alluri, S. Achanta, S.R. Kadiri, S.V. Gangashetty, and A.K. Vuppala, ”SFF Anti-Spoofer: IIIT-H Submission for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2017,” in
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
K. Choi, G. Fazekas, and M. Sandler, ”Automatic tagging using deep convolutional neural networks,”
2016
Cited alongside, same era.
ASVspoof2019:the automatic speaker verification spoofing and countermeasure.[Online]. www.asvspoof.org
Cited in the paper.
https://github.com/CVxTz/audio_classification
Cited in the paper.
ASVspoof2019:the automatic speaker verification spoofing and countermeasure challenge evaluation plan.[Online]. Available: http://www.asvspoof.org/asvspoof2019/asvspoof2019evaluation-
Cited in the paper.
2017
Later among the works it cites.
T. Kinnunen, K. Lee, H. Delgado, N. Evans, M. Todisco, M. Sahidullah, J. Yamagishi, and D.A. Reynolds, ”t-DCF: a detection cost function for the tandem assessment of spoofing countermeasures and automatic speaker verification,” in
2018
Later among the works it cites.