Lhotse: a speech data representation library for the modern deep learning ecosystem

The ami meeting corpus

Iain McCowan, Jean Carletta, Wessel Kraaij, Simone Ashby, S Bourban, M Flynn, M Guillemot, Thomas Hain, J Kadlec, Vasilis Karaiskos, et al · 2005

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The kaldi speech recognition toolkit

Daniel Povey, Arnab Ghoshal, Gilles Boulianne, Lukas Burget, Ondrej Glembek, Nagendra Goel, Mirko Hannemann, Petr Motlicek, Yanmin Qian, Petr Schwarz, et al · 2011

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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

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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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Espnet: End-to-end speech processing toolkit

Original

Shinji Watanabe, Takaaki Hori, Shigeki Karita, Tomoki Hayashi, Jiro Nishitoba, Yuya Unno, Nelson Enrique Yalta Soplin, Jahn Heymann, Matthew Wiesner, Nanxin Chen, et al · 2018

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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

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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 Mazaré, Julien Karadayi, Vitaliy Liptchinsky, Ronan Collobert, Christian Fuegen, et al · 2020

Cited alongside, same era.

MLS: A large-scale multilingual dataset for speech research

Vineel Pratap, Qiantong Xu, Anuroop Sriram, Gabriel Synnaeve, and Ronan Collobert · 2020

Cited alongside, same era.

Chime-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings

Original

Shinji Watanabe, Michael Mandel, Jon Barker, Emmanuel Vincent, Ashish Arora, Xuankai Chang, Sanjeev Khudanpur, Vimal Manohar, Daniel Povey, Desh Raj, et al · 2020

Cited alongside, same era.

https://github.com/k2-fsa/icefall

Icefall, 2021 · 2021

Cited alongside, same era.

https://github.com/k2-fsa/k2

k2: FSA/FST algorithms, differentiable, with PyTorch compatibility., 2021 · 2021

Cited alongside, same era.

https://github.com/danpovey/lilcom

lilcom, 2021 · 2021

Closest in time.

http://sox.sourceforge.net

SoX: the Swiss Army knife of sound processing programs, 2021 · 2021

Closest in time.

https://pytorch.org/audio/stable/index.html

torchaudio, 2021 · 2021

Closest in time.

Gigaspeech: An evolving, multi-domain asr corpus with 10,000 hours of transcribed audio

Guoguo Chen, Shuzhou Chai, Guanbo Wang, Jiayu Du, Wei-Qiang Zhang, Chao Weng, Dan Su, Daniel Povey, Jan Trmal, Junbo Zhang, et al · 2021

Closest in time.

The people’s speech: A large-scale diverse english speech recognition dataset for commercial usage

Daniel Galvez, Greg Diamos, Juan Manuel Ciro Torres, Keith Achorn, Anjali Gopi, David Kanter, Max Lam, Mark Mazumder, and Vijay Janapa Reddi · 2021

Closest in time.

Spgispeech: 5,000 hours of transcribed financial audio for fully formatted end-to-end speech recognition

Patrick K O’Neill, Vitaly Lavrukhin, Somshubra Majumdar, Vahid Noroozi, Yuekai Zhang, Oleksii Kuchaiev, Jagadeesh Balam, Yuliya Dovzhenko, Keenan Freyberg, Michael D Shulman, et al · 2021