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Speech enhancement is an essential task of improving speech quality in noise scenario.
“Visual contribution to speech intelligibility in noise,”
William H Sumby and Irwin Pollack, · 1954
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“All-pole modeling of degraded speech,”
Jae Lim and Alan Oppenheim, · 1978
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“Speech enhancement from noise: A regenerative approach,”
Markos Dendrinos, Stelios Bakamidis, and George Carayannis, · 1991
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“Spectral subtraction based on minimum statistics,”
Rainer Martin, · 1994
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“A signal subspace approach for speech enhancement,”
Yariv Ephraim and Harry L Van Trees, · 1995
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“Video assisted speech source separation,”
Wenwu Wang, Darren Cosker, Yulia Hicks, S Saneit, and Jonathon Chambers, · 2005
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“An audio-visual corpus for speech perception and automatic speech recognition,”
Martin Cooke, Jon Barker, Stuart Cunningham, and Xu Shao, · 2006
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Speech enhancement: theory and practice
Philipos C Loizou, · 2013
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“Conditional generative adversarial nets,”
Mehdi Mirza and Simon Osindero, · 2014
Cited alongside, same era.
“TCD-TIMIT: An audio-visual corpus of continuous speech,”
Naomi Harte and Eoin Gillen, · 2015
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“Audio-visual speech enhancement using deep neural networks,”
Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai, Jen-Chun Lin, Yu Tsao, Hsiu-Wen Chang, and Hsin-Min Wang, · 2016
Cited alongside, same era.
“Unsupervised representation learning with deep convolutional generative adversarial networks,”
Alec Radford, Luke Metz, and Soumith Chintala, · 2016
Cited alongside, same era.
“SEGAN: Speech enhancement generative adversarial network,”
Santiago Pascual, Antonio Bonafonte, and Joan Serrà, · 2017
Cited alongside, same era.
“Least squares generative adversarial networks,”
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley, · 2017
“Seeing through noise: Visually driven speaker separation and enhancement,”
Aviv Gabbay, Ariel Ephrat, Tavi Halperin, and Shmuel Peleg, · 2018
Later among the works it cites.
“On adversarial training and loss functions for speech enhancement,”
Ashutosh Pandey and Deliang Wang, · 2018
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“Visual speech enhancement,”
Aviv Gabbay, Asaph Shamir, and Shmuel Peleg, · 2018
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“Looking to listen at the cocktail party: A speaker-independent audio-visual model for speech separation,”
Ariel Ephrat, Inbar Mosseri, Oran Lang, Tali Dekel, Kevin Wilson, Avinatan Hassidim, William T Freeman, and Michael Rubinstein, · 2018
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“Sergan: Speech enhancement using relativistic generative adversarial networks with gradient penalty,”
Deepak Baby and Sarah Verhulst, · 2019
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“A robust audio-visual speech enhancement model,”
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Cited alongside, same era.
“Image-to-image translation with conditional adversarial networks,”
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros, · 2017
Cited alongside, same era.
Wupeng Wang, Chao Xing, Dong Wang, Xiao Chen, and Fengyu Sun, · 2020
Later among the works it cites.
“AV(SE) 2 : Audio-visual squeeze-excite speech enhancement,”
Michael L Iuzzolino and Kazuhito Koishida, · 2020
Later among the works it cites.