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We investigate the effectiveness of generative adversarial networks (GANs) for speech enhancement, in the context of improving noise robustness of automatic speech recognition (ASR) systems.
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“Recurrent neural networks for noise reduction in robust ASR,”
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“Generative adversarial nets,”
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“Conditional generative adversarial nets,”
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“Joint noise adaptive training for robust automatic speech recognition,”
Arun Narayanan and DeLiang Wang, · 2014
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“A regression approach to speech enhancement based on deep neural networks,”
Yong Xu, Jun Du, Li-Rong Dai, and Chin-Hui Lee, · 2015
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“Speech enhancement with lstm recurrent neural networks and its application to noise-robust asr,”
Felix Weninger, Hakan Erdogan, and · 2015
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“Deep neural network based spectral feature mapping for robust speech recognition,”
Kun Han, Yanzhang He, Deblin Bagchi, Eric Fosler-Lussier, and DeLiang Wang, · 2015
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“Improving robustness of deep neural network acoustic models via speech separation and joint adaptive training,”
Arun Narayanan and DeLiang Wang, · 2015
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“Context encoders: Feature learning by inpainting,”
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros, · 2016
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“Least squares generative adversarial networks,”
Xudong Mao, Qing Li, and · 2016
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“Deep multi-scale video prediction beyond mean square error,”
Michael Mathieu, Camille Couprie, and Yann LeCun, · 2016
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“SEGAN: Speech Enhancement Generative Adversarial Network,”
Santiago Pascual, Antonio Bonafonte, and Joan Serrà, · 2017
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“Image-to-image translation with conditional adversarial networks,”
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros, · 2017
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“Improved cepstra minimum-mean-square-error noise reduction algorithm for robust speech recognition,”
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William Chan, Navdeep Jaitly, Quoc V Le, and Oriol Vinyals, · 2015
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“Convolutional LSTM network: A machine learning approach for precipitation nowcasting,”
SHI Xingjian, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo, · 2015
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“Neural machine translation by jointly learning to align and translate,”
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio, · 2015
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“Neural Network Adaptive Beamforming for Robust Multichannel Speech Recognition,”
Bo Li, Tara N Sainath, Ron J Weiss, Kevin W Wilson, and Michiel Bacchiani, · 2016
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“Snr-aware convolutional neural network modeling for speech enhancement.,”
Szu-Wei Fu, Yu Tsao, and Xugang Lu, · 2016
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“Unsupervised representation learning with deep convolutional generative adversarial networks,”
Alec Radford, Luke Metz, and Soumith Chintala, · 2016
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Jinyu Li, Yan Huang, and Yifan Gong, · 2017
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“Supervised speech separation based on deep learning: an overview,”
DeLiang Wang and Jitong Chen, · 2017
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“Conditional generative adversarial networks for speech enhancement and noise-robust speaker verification,”
Daniel Michelsanti and Zheng-Hua Tan, · 2017
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“Generation of large-scale simulated utterances in virtual rooms to train deep-neural networks for far-field speech recognition in Google Home,”
Chanwoo Kim, Ananya Misra, Kean Chin, Thad Hughes, Arun Narayanan, Tara Sainath, and Michiel Bacchiani, · 2017
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“Very deep convolutional networks for end-to-end speech recognition,”
Yu Zhang, William Chan, and Navdeep Jaitly, · 2017
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“A comparison of sequence-to-sequence models for speech recognition,”
Rohit Prabhavalkar, Kanishka Rao, Tara N Sainath, Bo Li, Leif Johnson, and Navdeep Jaitly, · 2017
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