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Previous work has encouraged domain-invariance in deep speaker embedding by adversarially classifying the dataset or labelled environment to which the generated features belong.
Jee weon Jung, Hee-Soo Heo, Ju ho Kim, Hye jin Shim, and Ha-Jin Yu, · 1910
Earlier work this paper cites.
“Probabilistic linear discriminant analysis for inferences about identity,”
Simon J.D. Prince and James H Elder, · 2007
Earlier work this paper cites.
“Front end factor analysis for speaker verification,”
Najim Dehak, Patrick J. Kenny, Réda Dehak, Pierre Dumouchel, and Pierre Ouellet, · 2011
Earlier work this paper cites.
“Analysis of i-vector length normalization in speaker recognition systems,”
Daniel Garcia-Romero and Carol Espy-Wilson, · 2011
Earlier work this paper cites.
“Speaker diarization with PLDA i-vector scoring and unsupervised calibration,”
Gregory Sell and Daniel Garcia-Romero, · 2014
Earlier work this paper cites.
“Domain-adversarial training of neural networks,”
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor Lempitsky, Urun Dogan, Marius Kloft, Francesco Orabona, and Tatiana Tommasi, · 2015
Earlier work this paper cites.
“Adversarial multi-task learning of deep neural networks for robust speech recognition,”
Yusuke Shinohara, · 2016
Earlier work this paper cites.
“VoxCeleb: A large-scale speaker identification dataset,”
Arsha Nagrani, Joon Son Chung, and Andrew Zisserman, · 2017
Earlier work this paper cites.
“X-vectors: robust DNN embeddings for speaker recognition,”
David Snyder, Daniel Garcia-Romero, Gregory Sell, Daniel Povey, and Sanjeev Khudanpur, · 2018
Cited alongside, same era.
“Diarization is Hard: some experiences and lessons learned for the JHU team in the inaugural DIHARD challenge,”
Gregory Sell, David Snyder, Alan Mccree, Daniel Garcia-Romero, Jesús Villalba, Matthew Maciejewski, Vimal Manohar, Najim Dehak, Daniel Povey, Shinji Watanabe, and Sanjeev Khudanpur, · 2018
Cited alongside, same era.
“Wasserstein distance guided representation learning for domain adaptation,”
Jian Shen, Yanru Qu, Weinan Zhang, and Yong Yu, · 2018
Cited alongside, same era.
“Voxceleb2: Deep speaker recognition,”
Joon Son Chung, Arsha Nagrani, and Andrew Zisserman, · 2018
Cited alongside, same era.
“Attentive statistics pooling for deep speaker embedding,”
Koji Okabe, Takafumi Koshinaka, and Koichi Shinoda, · 2018
Cited alongside, same era.
“Additive margin softmax for face verification,”
“Adversarial speaker verification,”
Zhong Meng, Yong Zhao, Jinyu Li, and Yifan Gong, · 2019
Closest in time.
“Variational domain adversarial learning for speaker verification,”
Youzhi Tu, Man-Wai Mak, and Jen-Tzung Chien, · 2019
Closest in time.
“Generative adversarial speaker embedding networks for domain robust end-to-end speaker verification,”
Gautam Bhattacharya, Joao Monteiro, Jahangir Alam, and Patrick Kenny, · 2019
Closest in time.
“SiGAN: Siamese generative adversarial network for identity-preserving face hallucination,”
Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su, and Gene Cheung, · 2019
Closest in time.
“LSTM based similarity measurement with spectral clustering for speaker diarization,”
Qingjian Lin, Ruiqing Yin, Ming Li, Hervé Bredin, and Claude Barras, · 2019
Closest in time.
“Fully supervised speaker diarization,”
A. Zhang, Q. Wang, Z. Zhu, J. Paisley, and C. Wang, · 2019
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Feng Wang, Jian Cheng, Weiyang Liu, and Haijun Liu, · 2018
Cited alongside, same era.
“ based x-vector clustering for speaker diarization,”
Mireia Diez, Lukáš Burget, Shuai Wang, and Johan Rohdin, · 2019
Cited alongside, same era.
Closest in time.
“Utterance-level aggregation for speaker recognition in the wild,”
W. Xie, A. Nagrani, J. S. Chung, and A. Zisserman, · 2019
Closest in time.