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Recent advances suggest the advantage of multi-modal training in comparison with single-modal methods.
Speech and language processing (2nd edition)
Daniel Jurafsky and James H. Martin · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Esc: Dataset for environmental sound classification
Karol J Piczak · 2015
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Audio set: An ontology and human-labeled dataset for audio events
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter · 2017
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Cnn architectures for large-scale audio classification
Shawn Hershey, Sourish Chaudhuri, Daniel PW Ellis, Jort F Gemmeke, Aren Jansen, R Channing Moore, Manoj Plakal, Devin Platt, Rif A Saurous, Bryan Seybold, et al · 2017
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Look, listen and learn
Relja Arandjelovic and Andrew Zisserman · 2017
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Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
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Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Unsupervised learning of semantic audio representations
Aren Jansen, Manoj Plakal, Ratheet Pandya, Daniel PW Ellis, Shawn Hershey, Jiayang Liu, R Channing Moore, and Rif A Saurous · 2018
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Objects that sound
Relja Arandjelovic and Andrew Zisserman · 2018
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Cooperative learning of audio and video models from self-supervised synchronization
Bruno Korbar, Du Tran, and Lorenzo Torresani · 2018
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Audio-visual scene analysis with self-supervised multisensory features
Andrew Owens and Alexei A Efros · 2018
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Learning representations by maximizing mutual information across views
Philip Bachman, R Devon Hjelm, and William Buchwalter · 2019
Cited alongside, same era.
wav2vec: Unsupervised pre-training for speech recognition
Steffen Schneider, Alexei Baevski, Ronan Collobert, and Michael Auli · 2019
Cited alongside, same era.
vq-wav2vec: Self-supervised learning of discrete speech representations
Alexei Baevski, Steffen Schneider, and Michael Auli · 2019
Cited alongside, same era.
A comparison of five multiple instance learning pooling functions for sound event detection with weak labeling
Yun Wang, Juncheng Li, and Florian Metze · 2019
Cited alongside, same era.
A deep residual network for large-scale acoustic scene analysis
Logan Ford, Hao Tang, François Grondin, and James R Glass · 2019
Cited alongside, same era.
Self-supervised learning by cross-modal audio-video clustering
Learning robust and multilingual speech representations
Kazuya Kawakami, Luyu Wang, Chris Dyer, Phil Blunsom, and Aäron van den Oord · 2020
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Unsupervised pretraining transfers well across languages
Morgane Rivière, Armand Joulin, Pierre-Emmanuel Mazaré, and Emmanuel Dupoux · 2020
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Libri-light: A benchmark for asr with limited or no supervision
Jacob Kahn, Morgane Rivière, Weiyi Zheng, Evgeny Kharitonov, Qiantong Xu, Pierre-Emmanuel Mazaré, Julien Karadayi, Vitaliy Liptchinsky, Ronan Collobert, Christian Fuegen, et al · 2020
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wav2vec 2.0: A framework for self-supervised learning of speech representations
Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
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Panns: Large-scale pretrained audio neural networks for audio pattern recognition
Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, and Mark D Plumbley · 2020
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Humam Alwassel, Dhruv Mahajan, Lorenzo Torresani, Bernard Ghanem, and Du Tran · 2019
Cited alongside, same era.
Specaugment: A simple data augmentation method for automatic speech recognition
Daniel S Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D Cubuk, and Quoc V Le · 2019
Cited alongside, same era.
Data-efficient image recognition with contrastive predictive coding
Olivier Henaff · 2020
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Cited alongside, same era.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Cited alongside, same era.
Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey Hinton · 2020
Cited alongside, same era.
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Contrastive predictive coding of audio with an adversary
Luyu Wang, Kazuya Kawakami, and Aäron van den Oord · 2020
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Coincidence, categorization, and consolidation: Learning to recognize sounds with minimal supervision
Aren Jansen, Daniel PW Ellis, Shawn Hershey, R Channing Moore, Manoj Plakal, Ashok C Popat, and Rif A Saurous · 2020
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Self-supervised multimodal versatile networks
Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelović, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, and Andrew Zisserman · 2020
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Audio-visual instance discrimination with cross-modal agreement
Pedro Morgado, Nuno Vasconcelos, and Ishan Misra · 2020
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Multi-modal self-supervision from generalized data transformations
Mandela Patrick, Yuki M. Asano, Ruth Fong, João F. Henriques, Geoffrey Zweig, and Andrea Vedaldi · 2020
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Data augmenting contrastive learning of speech representations in the time domain
Eugene Kharitonov, Morgane Rivière, Gabriel Synnaeve, Lior Wolf, Pierre-Emmanuel Mazaré, Matthijs Douze, and Emmanuel Dupoux · 2020
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