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Speech restoration aims to remove distortions in speech signals.
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Digital audio restoration
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Two-stage deep learning for noisy-reverberant speech enhancement
Yan Zhao, Zhong-Qiu Wang, and DeLiang Wang · 2002
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Audio analysis and spectral restoration workflows using adobe audition
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What is the best multi-stage architecture for object recognition?
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio Ranzato, and Yann LeCun · 2009
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Speech enhancement with multichannel wiener filter techniques in multimicrophone binaural hearing aids
Tim Van den Bogaert, Simon Doclo, Jan Wouters, and Marc Moonen · 2009
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Speech dereverberation
Patrick A Naylor and Nikolay D Gaubitch · 2010
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The REVERB challenge: A common evaluation framework for dereverberation and recognition of reverberant speech
Keisuke Kinoshita, Marc Delcroix, Takuya Yoshioka, Tomohiro Nakatani, Emanuel Habets, Reinhold Haeb-Umbach, Volker Leutnant, Armin Sehr, Walter Kellermann, and Roland Maas · 2013
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Ideal ratio mask estimation using deep neural networks for robust speech recognition
Arun Narayanan and DeLiang Wang · 2013
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Joint dereverberation and noise reduction using beamforming and a single-channel speech enhancement scheme
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Online speech dereverberation using kalman filter and em algorithm
Boaz Schwartz, Sharon Gannot, and Emanuël AP Habets · 2014
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Detection and reconstruction of clipped speech for speaker recognition
Fanhu Bie, Dong Wang, Jun Wang, and Thomas Fang Zheng · 2015
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Fast and accurate deep network learning by exponential linear units
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Learning spectral mapping for speech dereverberation and denoising
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Sparsity and cosparsity for audio declipping: a flexible non-convex approach
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A deep neural network approach to speech bandwidth expansion
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U-net: Convolutional networks for biomedical image segmentation
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World: a vocoder-based high-quality speech synthesis system for real-time applications
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Waveglow: A flow-based generative network for speech synthesis
Ryan Prenger, Rafael Valle, and Bryan Catanzaro · 2019
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FastSpeech: Fast, robust and controllable text to speech
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Sparse recovery and dictionary learning from nonlinear compressive measurements
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Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92)
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Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
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A study of speech distortion conditions in real scenarios for speech processing applications
Dayana Ribas, Emmanuel Vincent, and José Ramón Calvo · 2016
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First step towards end-to-end parametric tts synthesis: Generating spectral parameters with neural attention
Wenfu Wang, Shuang Xu, and Bo Xu · 2016
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Audio super resolution using neural networks
Volodymyr Kuleshov, S Zayd Enam, and Stefano Ermon · 2017
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SEGAN: Speech enhancement generative adversarial network
Santiago Pascual, Antonio Bonafonte, and Joan Serra · 2017
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Noisy speech database for training speech enhancement algorithms and TTS models
Cassia Valentini-Botinhao et al · 2017
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An analysis of environment, microphone and data simulation mismatches in robust speech recognition
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Psychoacoustically motivated audio declipping based on weighted l 1 minimization
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Real time speech enhancement in the waveform domain
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Masking and inpainting: A two-stage speech enhancement approach for low snr and non-stationary noise
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DCCRN: Deep complex convolution recurrent network for phase-aware speech enhancement
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Channel-wise subband input for better voice and accompaniment separation on high resolution music
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Waveflow: A compact flow-based model for raw audio
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Aishell-3: A multi-speaker mandarin tts corpus and the baselines
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On filter generalization for music bandwidth extension using deep neural networks
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Audio-visual speech separation and dereverberation with a two-stage multimodal network
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Qiao Tian, Yi Chen, Zewang Zhang, Heng Lu, Linghui Chen, Lei Xie, and Shan Liu · 2020
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Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram
Ryuichi Yamamoto, Eunwoo Song, and Jae-Min Kim · 2020
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A survey and an extensive evaluation of popular audio declipping methods
Pavel Záviška, Pavel Rajmic, Alexey Ozerov, and Lucas Rencker · 2020
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Acoustic echo cancellation challenge
Ross Cutler, Ando Saabas, Tanel Parnamaa, Markus Loide, Sten Sootla, Marju Purin, Hannes Gamper, Sebastian Braun, Karsten Sorensen, Robert Aichner, et al · 2021
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