Fetching the paper…
Reading the bibliography…
Deep embedding based text-independent speaker verification has demonstrated superior performance to traditional methods in many challenging scenarios.
J. S. Chung, A. Nagrani, and A. Zisserman, “Voxceleb2: Deep speaker recognition,” in
1929
Earlier work this paper cites.
D. Povey, A. Ghoshal, G. Boulianne, L. Burget, O. Glembek, N. Goel, M. Hannemann, P. Motlicek, Y. Qian, P. Schwarz
2011
Earlier work this paper cites.
G. Heigold, I. Moreno, S. Bengio, and N. Shazeer, “End-to-end text-dependent speaker verification,” in
2016
Earlier work this paper cites.
M. McLaren, L. Ferrer, D. Castan, and A. Lawson, “The speakers in the wild (sitw) speaker recognition database.” in
2016
Earlier work this paper cites.
L. Li, Y. Chen, Y. Shi, Z. Tang, and D. Wang, “Deep speaker feature learning for text-independent speaker verification,”
2017
Earlier work this paper cites.
G. Bhattacharya, M. J. Alam, and P. Kenny, “Deep speaker embeddings for short-duration speaker verification.” in
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
A. Nagrani, J. S. Chung, and A. Zisserman, “Voxceleb: A large-scale speaker identification dataset,”
2017
Earlier work this paper cites.
D. Snyder, D. Garcia-Romero, G. Sell, D. Povey, and S. Khudanpur, “X-vectors: Robust dnn embeddings for speaker recognition,” in
2018
Earlier work this paper cites.
J.-W. Jung, H.-S. Heo, I.-H. Yang, H.-J. Shim, and H.-J. Yu, “A complete end-to-end speaker verification system using deep neural networks: From raw signals to verification result,” in
2018
Cited alongside, same era.
Y. Zhu, T. Ko, D. Snyder, B. Mak, and D. Povey, “Self-attentive speaker embeddings for text-independent speaker verification,”
2018
Cited alongside, same era.
W. Cai, J. Chen, and M. Li, “Exploring the encoding layer and loss function in end-to-end speaker and language recognition system,” in
2018
Cited alongside, same era.
C. Zhang, K. Koishida, and J. H. Hansen, “Text-independent speaker verification based on triplet convolutional neural network embeddings,”
2018
Cited alongside, same era.
L. Wan, Q. Wang, A. Papir, and I. L. Moreno, “Generalized end-to-end loss for speaker verification,” in
2018
Cited alongside, same era.
Y. Tang, G. Ding, J. Huang, X. He, and B. Zhou, “Deep speaker embedding learning with multi-level pooling for text-independent speaker verification,” in
2019
Closest in time.
Z. Gao, Y. Song, I. McLoughlin, P. Li, Y. Jiang, and L. Dai, “Improving aggregation and loss function for better embedding learning in end-to-end speaker verification system,”
2019
Closest in time.
S. Wang, Z. Huang, Y. Qian, and K. Yu, “Discriminative neural embedding learning for short-duration text-independent speaker verification,”
2019
Closest in time.
R. Li, N. Li, D. Tuo, M. Yu, D. Su, and D. Yu, “Boundary discriminative large margin cosine loss for text-independent speaker verification,” in
2019
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Novoselov, V. Shchemelinin, A. Shulipa, A. Kozlov, and I. Kremnev, “Triplet loss based cosine similarity metric learning for text-independent speaker recognition,”
2018
Cited alongside, same era.
D. Snyder, D. Garcia-Romero, G. Sell, A. McCree, D. Povey, and S. Khudanpur, “Speaker recognition for multi-speaker conversations using x-vectors,” in
2019
Cited alongside, same era.
W. Xie, A. Nagrani, J. S. Chung, and A. Zisserman, “Utterance-level aggregation for speaker recognition in the wild,” in
2019
Cited alongside, same era.
J. Villalba, N. Chen, D. Snyder, D. Garcia-Romero, A. McCree, G. Sell, J. Borgstrom, F. Richardson, S. Shon, F. Grondin
2019
Cited alongside, same era.
2019
Closest in time.
Y. Liu, L. He, and J. Liu, “Large margin softmax loss for speaker verification,” in
2019
Closest in time.
V. Mingote, A. Miguel, D. Ribas, A. Ortega, and E. Lleida, “Optimization of false acceptance/rejection rates and decision threshold for end-to-end text-dependent speaker verification systems,”
2019
Closest in time.