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Generative models have gained more and more attention in recent years for their remarkable success in tasks that required estimating and sampling data distribution to generate high-fidelity synthetic data.
Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs
Antony W Rix, John G Beerends, Michael P Hollier, and Andries P Hekstra · 2001
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Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
Alex Graves, Santiago Fernández, Faustino Gomez, and Jürgen Schmidhuber · 2006
Earlier work this paper cites.
Evaluation of objective quality measures for speech enhancement
Yi Hu and Philipos C Loizou · 2007
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CrowdMOS: An approach for crowdsourcing mean opinion score studies
Flávio Ribeiro, Dinei Florêncio, Cha Zhang, and Michael Seltzer · 2011
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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Librispeech: An asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep clustering: Discriminative embeddings for segmentation and separation
John R Hershey, Zhuo Chen, Jonathan Le Roux, and Shinji Watanabe · 2016
Earlier work this paper cites.
An algorithm for predicting the intelligibility of speech masked by modulated noise maskers
Jesper Jensen and Cees H Taal · 2016
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Montreal forced aligner: Trainable text-speech alignment using kaldi
Michael McAuliffe, Michaela Socolof, Sarah Mihuc, Michael Wagner, and Morgan Sonderegger · 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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Ashish Vaswani, Noam M. Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Permutation invariant training of deep models for speaker-independent multi-talker speech separation
Dong Yu, Morten Kolbæk, Zheng-Hua Tan, and Jesper Jensen · 2017
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torchdiffeq, 2018
Ricky T. Q. Chen · 2018
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Neural ordinary differential equations
Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, and David Kristjanson Duvenaud · 2018
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Transfer learning from speaker verification to multispeaker text-to-speech synthesis
Ye Jia, Yu Zhang, Ron Weiss, Quan Wang, Jonathan Shen, Fei Ren, Patrick Nguyen, Ruoming Pang, Ignacio Lopez Moreno, Yonghui Wu, et al · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Natural tts synthesis by conditioning wavenet on mel spectrogram predictions
Jonathan Shen, Ruoming Pang, Ron J Weiss, Mike Schuster, Navdeep Jaitly, Zongheng Yang, Zhifeng Chen, Yu Zhang, Yuxuan Wang, Rj Skerrv-Ryan, et al · 2018
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Semi-supervised training for improving data efficiency in end-to-end speech synthesis
Yu-An Chung, Yuxuan Wang, Wei-Ning Hsu, Yu Zhang, and RJ Skerry-Ryan · 2019
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Semi-supervised generative modeling for controllable speech synthesis
Raza Habib, Soroosh Mariooryad, Matt Shannon, Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton, David Kao, and Tom Bagby · 2019
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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 Mazar’e, Julien Karadayi, Vitaliy Liptchinsky, Ronan Collobert, Christian Fuegen, Tatiana Likhomanenko, Gabriel Synnaeve, Armand Joulin, Abdel rahman Mohamed, and Emmanuel Dupoux · 2019
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Sdr–half-baked or well done?
Jonathan Le Roux, Scott Wisdom, Hakan Erdogan, and John R Hershey · 2019
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Conv-tasnet: Surpassing ideal time–frequency magnitude masking for speech separation
Yi Luo and Nima Mesgarani · 2019
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The m-ailabs speech dataset – caito, 2017
Munich Artificial Intelligence Laboratories GmbH · 2019
Earlier work this paper cites.
Waveglow: A flow-based generative network for speech synthesis
Ryan Prenger, Rafael Valle, and Bryan Catanzaro · 2019
Cited alongside, same era.
Wham!: Extending speech separation to noisy environments
Gordon Wichern, Joe Antognini, Michael Flynn, Licheng Richard Zhu, Emmett McQuinn, Dwight Crow, Ethan Manilow, and Jonathan Le Roux · 2019
Cited alongside, same era.
CSTR VCTK Corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92)
Junichi Yamagishi, Christophe Veaux, and Kirsten MacDonald · 2019
Cited alongside, same era.
Libritts: A corpus derived from librispeech for text-to-speech
Heiga Zen, Viet Dang, Rob Clark, Yu Zhang, Ron J Weiss, Ye Jia, Zhifeng Chen, and Yonghui Wu · 2019
Cited alongside, same era.
wav2vec 2.0: A framework for self-supervised learning of speech representations
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
On generative spoken language modeling from raw audio
Kushal Lakhotia, Evgeny Kharitonov, Wei-Ning Hsu, Yossi Adi, Adam Polyak, Benjamin Bolte, Tu Nguyen, Jade Copet, Alexei Baevski, Adel Ben Mohamed, and Emmanuel Dupoux · 2021
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A study on speech enhancement based on diffusion probabilistic model
Yen-Ju Lu, Yu Tsao, and Shinji Watanabe · 2021
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Speech resynthesis from discrete disentangled self-supervised representations
Adam Polyak, Yossi Adi, Jade Copet, Eugene Kharitonov, Kushal Lakhotia, Wei-Ning Hsu, Abdelrahman Mohamed, and Emmanuel Dupoux · 2021
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Train short, test long: Attention with linear biases enables input length extrapolation
Ofir Press, Noah A. Smith, and Mike Lewis · 2021
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SpeechBrain: A general-purpose speech toolkit, 2021
Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, Ju-Chieh Chou, Sung-Lin Yeh, Szu-Wei Fu, Chien-Feng Liao, Elena Rastorgueva, François Grondin, William Aris, Hwidong Na, Yan Gao, Renato De Mori, and Yoshua Bengio · 2021
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Cited alongside, same era.
Wavegrad: Estimating gradients for waveform generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan · 2020
Cited alongside, same era.
Generative pre-training for speech with autoregressive predictive coding
Yu-An Chung and James Glass · 2020
Cited alongside, same era.
Librimix: An open-source dataset for generalizable speech separation
Joris Cosentino, Manuel Pariente, Samuele Cornell, Antoine Deleforge, and Emmanuel Vincent · 2020
Cited alongside, same era.
Real time speech enhancement in the waveform domain
Alexandre Défossez, Gabriel Synnaeve, and Yossi Adi · 2020
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis
Jungil Kong, Jaehyeon Kim, and Jaekyoung Bae · 2020
Cited alongside, same era.
Later among the works it cites.
Fastspeech 2: Fast and high-quality end-to-end text to speech
Yi Ren, Chenxu Hu, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, and Tie-Yan Liu · 2021
Later among the works it cites.
Attention is all you need in speech separation
Cem Subakan, Mirco Ravanelli, Samuele Cornell, Mirko Bronzi, and Jianyuan Zhong · 2021
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Superb: Speech processing universal performance benchmark
Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang, Cheng-I Jeff Lai, Kushal Lakhotia, Yist Y Lin, Andy T Liu, Jiatong Shi, Xuankai Chang, Guan-Ting Lin, et al · 2021
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A3T: Alignment-aware acoustic and text pretraining for speech synthesis and editing
He Bai, Renjie Zheng, Junkun Chen, Xintong Li, Mingbo Ma, and Liang Huang · 2022
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AudioLM: a language modeling approach to audio generation
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matthew Sharifi, Olivier Teboul, David Grangier, Marco Tagliasacchi, and Neil Zeghidour · 2022
Later among the works it cites.
Tts-portuguese corpus: a corpus for speech synthesis in brazilian portuguese
Edresson Casanova, Arnaldo Candido Junior, Christopher Shulby, Frederico Santos de Oliveira, João Paulo Teixeira, Moacir Antonelli Ponti, and Sandra Aluísio · 2022
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Wavlm: Large-scale self-supervised pre-training for full stack speech processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, et al · 2022
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High fidelity neural audio compression
Alexandre Défossez, Jade Copet, Gabriel Synnaeve, and Yossi Adi · 2022
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Specgrad: Diffusion probabilistic model based neural vocoder with adaptive noise spectral shaping
Yuma Koizumi, Heiga Zen, Kohei Yatabe, Nanxin Chen, and Michiel Bacchiani · 2022
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Conditional diffusion probabilistic model for speech enhancement
Yen-Ju Lu, Zhong-Qiu Wang, Shinji Watanabe, Alexander Richard, Cheng Yu, and Yu Tsao · 2022
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Generative spoken dialogue language modeling
Tu Nguyen, Eugene Kharitonov, Jade Copet, Yossi Adi, Wei-Ning Hsu, Ali Mamdouh Elkahky, Paden Tomasello, Robin Algayres, Benoît Sagot, Abdelrahman Mohamed, and Emmanuel Dupoux · 2022
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Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang, Zili Huang, Kushal Lakhotia, Shu-wen Yang, Shuyan Dong, Andy T Liu, Cheng-I Jeff Lai, Jiatong Shi, et al · 2022
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Soundstream: An end-to-end neural audio codec
Neil Zeghidour, Alejandro Luebs, Ahmed Omran, Jan Skoglund, and Marco Tagliasacchi · 2022
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Voicebox: Text-guided multilingual universal speech generation at scale
Matthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari, Rashel Moritz, Mary Williamson, Vimal Manohar, Yossi Adi, Jay Mahadeokar, et al · 2023
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Flow matching for generative modeling
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matthew Le · 2023
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Speech enhancement and dereverberation with diffusion-based generative models
Julius Richter, Simon Welker, Jean-Marie Lemercier, Bunlong Lay, and Timo Gerkmann · 2023
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Diffusion-based generative speech source separation
Robin Scheibler, Youna Ji, Soo-Whan Chung, Jaeuk Byun, Soyeon Choe, and Min-Seok Choi · 2023
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Exploring self-attention mechanisms for speech separation
Cem Subakan, Mirco Ravanelli, Samuele Cornell, François Grondin, and Mirko Bronzi · 2023
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Neural codec language models are zero-shot text to speech synthesizers
Chengyi Wang, Sanyuan Chen, Yu Wu, Zi-Hua Zhang, Long Zhou, Shujie Liu, Zhuo Chen, Yanqing Liu, Huaming Wang, Jinyu Li, Lei He, Sheng Zhao, and Furu Wei · 2023
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