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We proposed a novel machine learning framework to conduct real-time multi-speaker diarization and recognition without prior registration and pretraining in a fully online learning setting.
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“Bandit problems with infinitely many arms,”
Donald A Berry, Robert W Chen, Alan Zame, David C Heath, and Larry A Shepp, · 1997
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“The nist 1999 speaker recognition evaluation—an overview,”
Alvin Martin and Mark Przybocki, · 2000
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“Speaker identification using mel frequency cepstral coefficients,”
Md Rashidul Hasan, Mustafa Jamil, MGRMS Rahman, et al., · 2004
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“Contextual bandit with adaptive feature extraction,”
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi, and Irina Rish, · 2006
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“The epoch-greedy algorithm for contextual multi-armed bandits,”
John Langford and Tong Zhang, · 2007
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“Online semi-supervised learning: Application to dynamic learning from radar data,”
B. Yver, · 2009
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“A contextual-bandit approach to personalized news article recommendation,”
Lihong Li, Wei Chu, John Langford, and Robert E Schapire, · 2010
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“A sticky hdp-hmm with application to speaker diarization,”
Emily Fox, Erik Sudderth, Michael Jordan, and Alan Willsky, · 2011
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“Speaker diarization: A review of recent research,”
X. Anguera, S. Bozonnet, N. Evans, C. Fredouille, G. Friedland, and O. Vinyals, · 2012
Cited alongside, same era.
“Unsupervised methods for speaker diarization: An integrated and iterative approach,”
Stephen H Shum, Najim Dehak, Réda Dehak, and James Glass, · 2013
Cited alongside, same era.
“A study of the cosine distance-based mean shift for telephone speech diarization,”
Mohammed Senoussaoui, Patrick Kenny, Themos Stafylakis, and Pierre Dumouchel, · 2013
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“Thompson sampling for contextual bandits with linear payoffs,”
Shipra Agrawal and Navin Goyal, · 2013
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“Return of the devil in the details: Delving deep into convolutional nets,”
Ken Chatfield, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, · 2014
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“Diarization resegmentation in the factor analysis subspace,”
“Speaker diarization using convolutional neural network for statistics accumulation refinement.,”
Z. Zajíc, M. Hrúz, and L. Müller, · 2017
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“X-vectors: Robust dnn embeddings for speaker recognition,”
David Snyder, Daniel Garcia-Romero, Gregory Sell, Daniel Povey, and Sanjeev Khudanpur, · 2018
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“Speaker diarization with lstm,”
Quan Wang, Carlton Downey, Li Wan, Philip Andrew Mansfield, and Ignacio Lopz Moreno, · 2018
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“Fully supervised speaker diarization,”
Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, and Chong Wang, · 2019
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“Voxceleb: Large-scale speaker verification in the wild,”
Arsha Nagrani, Joon Son Chung, Weidi Xie, and Andrew Zisserman, · 2019
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“VoiceID on the fly: A speaker recognition system that learns from scratch,”
Baihan Lin and Xinxin Zhang, · 2020
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Gregory Sell and Daniel Garcia-Romero, · 2015
Cited alongside, same era.
“The speakers in the wild (sitw) speaker recognition database.,”
Mitchell McLaren, Luciana Ferrer, Diego Castan, and Aaron Lawson, · 2016
Cited alongside, same era.
“Speaker identification features extraction methods: A systematic review,”
Sreenivas Sremath Tirumala, Seyed Reza Shahamiri, Abhimanyu Singh Garhwal, and Ruili Wang, · 2017
Cited alongside, same era.
“Voxceleb: a large-scale speaker identification dataset,”
A. Nagrani, J. S. Chung, and A. Zisserman, · 2017
Cited alongside, same era.
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“Unified models of human behavioral agents in bandits, contextual bandits and rl,”
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf, Jenna Reinen, and Irina Rish, · 2020
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“Online learning in iterated prisoner’s dilemma to mimic human behavior,”
Baihan Lin, Djallel Bouneffouf, and Guillermo Cecchi, · 2020
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“Online semi-supervised learning in contextual bandits with episodic reward,”
Baihan Lin, · 2020
Closest in time.