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This document describes version 0.10 of TorchAudio: building blocks for machine learning applications in the audio and speech processing domain.
“Deep speech: Scaling up end-to-end speech recognition,”
Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, et al., · 2014
Earlier work this paper cites.
“TensorFlow: Large-scale machine learning on heterogeneous systems,” 2015,
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng, · 2015
Earlier work this paper cites.
“librosa: Audio and music signal analysis in python,”
Brian McFee, Colin Raffel, Dawen Liang, Daniel PW Ellis, Matt McVicar, Eric Battenberg, and Oriol Nieto, · 2015
Earlier work this paper cites.
“Librispeech: an asr corpus based on public domain audio books,”
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur, · 2015
Earlier work this paper cites.
“Wav2letter: an end-to-end convnet-based speech recognition system,”
Ronan Collobert, Christian Puhrsch, and Gabriel Synnaeve, · 2016
Earlier work this paper cites.
“The lj speech dataset,”
Keith Ito and Linda Johnson, · 2017
Earlier work this paper cites.
“ESPnet: End-to-end speech processing toolkit,”
Shinji Watanabe, Takaaki Hori, Shigeki Karita, Tomoki Hayashi, Jiro Nishitoba, Yuya Unno, Nelson Enrique Yalta Soplin, Jahn Heymann, Matthew Wiesner, Nanxin Chen, Adithya Renduchintala, and Tsubasa Ochiai, · 2018
Earlier work this paper cites.
“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
Earlier work this paper cites.
“Efficient neural audio synthesis,”
Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aaron Oord, Sander Dieleman, and Koray Kavukcuoglu, · 2018
Cited alongside, same era.
“Pytorch: An imperative style, high-performance deep learning library,”
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala, · 2019
Cited alongside, same era.
“Espresso: A fast end-to-end neural speech recognition toolkit,”
Yiming Wang, Tongfei Chen, Hainan Xu, Shuoyang Ding, Hang Lv, Yiwen Shao, Nanyun Peng, Lei Xie, Shinji Watanabe, and Sanjeev Khudanpur, · 2019
Cited alongside, same era.
“fairseq: A fast, extensible toolkit for sequence modeling,”
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli, · 2019
Cited alongside, same era.
“Nemo: a toolkit for building ai applications using neural modules,”
“Waveglow: A flow-based generative network for speech synthesis,”
Ryan Prenger, Rafael Valle, and Bryan Catanzaro, · 2019
Later among the works it cites.
“Array programming with NumPy,”
Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Río, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke, and Travis E. Oliphant, · 2020
Later among the works it cites.
“Ddsp: Differentiable digital signal processing,”
Jesse Engel, Lamtharn (Hanoi) Hantrakul, Chenjie Gu, and Adam Roberts, · 2020
Later among the works it cites.
“Asteroid: the PyTorch-based audio source separation toolkit for researchers,”
Manuel Pariente, Samuele Cornell, Joris Cosentino, Sunit Sivasankaran, Efthymios Tzinis, Jens Heitkaemper, Michel Olvera, Fabian-Robert Stöter, Mathieu Hu, Juan M. Martín-Doñas, David Ditter, Ariel Frank, Antoine Deleforge, and Emmanuel Vincent, · 2020
Later among the works it cites.
“wav2vec 2.0: A framework for self-supervised learning of speech representations,”
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli, · 2020
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Oleksii Kuchaiev, Jason Li, Huyen Nguyen, Oleksii Hrinchuk, Ryan Leary, Boris Ginsburg, Samuel Kriman, Stanislav Beliaev, Vitaly Lavrukhin, Jack Cook, et al., · 2019
Cited alongside, same era.
“The pytorch-kaldi speech recognition toolkit,”
M. Ravanelli, T. Parcollet, and Y. Bengio, · 2019
Cited alongside, same era.
“Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92),” 2019
Junichi Yamagishi, Christophe Veaux, Kirsten MacDonald, et al., · 2019
Cited alongside, same era.
“Conv-tasnet: Surpassing ideal time–frequency magnitude masking for speech separation,”
Yi Luo and Nima Mesgarani, · 2019
Cited alongside, same era.
Later among the works it cites.
“Speechbrain: A general-purpose speech toolkit,”
Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, et al., · 2021
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“Hubert: Self-supervised speech representation learning by masked prediction of hidden units,”
Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed, · 2021
Closest in time.