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Incremental improvements in accuracy of Convolutional Neural Networks are usually achieved through use of deeper and more complex models trained on larger datasets.
“An overview of text-independent speaker recognition: From features to supervectors,”
Tomi Kinnunen and Haizhou Li, · 2010
Earlier work this paper cites.
“Understanding the difficulty of training deep feedforward neural networks,”
Xavier Glorot and Yoshua Bengio, · 2010
Earlier work this paper cites.
“Dropout: A simple way to prevent neural networks from overfitting,”
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov, · 2014
Earlier work this paper cites.
“Deep residual learning for image recognition,”
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, · 2015
Earlier work this paper cites.
“Facenet: A unified embedding for face recognition and clustering,”
Florian Schroff, Dmitry Kalenichenko, and James Philbin, · 2015
Earlier work this paper cites.
“Voxceleb: a large-scale speaker identification dataset,”
Arsha Nagrani, Joon Son Chung, and Andrew Zisserman, · 2017
Cited alongside, same era.
“Deep speaker: an end-to-end neural speaker embedding system,”
Chao Li, Xiaokong Ma, Bing Jiang, Xiangang Li, Xuewei Zhang, Xiao Liu, Ying Cao, Ajay Kannan, and Zhenyao Zhu, · 2017
Cited alongside, same era.
“Sphereface: Deep hypersphere embedding for face recognition,”
Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, and Le Song, · 2017
Cited alongside, same era.
“Deep speaker: an end-to-end neural speaker embedding system,”
Chao Li, Xiaokong Ma, Bing Jiang, Xiangang Li, Xuewei Zhang, Xiao Liu, Ying Cao, Ajay Kannan, and Zhenyao Zhu, · 2017
Cited alongside, same era.
“Promoting robustness for speaker modeling in the community: the prism evaluation set,”
“Voxceleb2: Deep speaker recognition,”
J. S. Chung, A. Nagrani, and A. Zisserman, · 2018
Closest in time.
Weicheng Cai, Jinkun Chen, and Ming Li, · 2018
Closest in time.
“Attentive statistics pooling for deep speaker embedding,”
Koji Okabe, Takafumi Koshinaka, and Koichi Shinoda, · 2018
Closest in time.
“Additive margin softmax for face verification,”
Feng Wang, Jian Cheng, Weiyang Liu, and Haijun Liu, · 2018
Closest in time.
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Luciana Ferrer, Harry Bratt, Lukas Burget, Honza Cernocky, Ondrej Glembek, Martin Graciarena, Aaron Lawson, Yun Lei, Pavel Matejka, Olda Plchot, et al.,
Cited in the paper.
“Squeeze-and-excitation networks,”
Jie Hu, Li Shen, and Gang Sun,
Cited in the paper.