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Non-autoregressive models greatly improve decoding speed over typical sequence-to-sequence models, but suffer from degraded performance.
Listen and fill in the missing letters: Non-autoregressive transformer for speech recognition
Nanxin Chen, Shinji Watanabe, Jesús Villalba, and Najim Dehak. 2020 · 1911
Earlier work this paper cites.
The design for the Wall Street Journal-based CSR corpus
Douglas B. Paul and Janet M. Baker. 1992 · 1992
Earlier work this paper cites.
Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks
Alex Graves, Santiago Fernández, Faustino J. Gomez, and Jürgen Schmidhuber. 2006 · 2006
Earlier work this paper cites.
Deep encoder, shallow decoder: Reevaluating the speed-quality tradeoff in machine translation
Jungo Kasai, Nikolaos Pappas, Hao Peng, James Cross, and Noah A. Smith. 2020 · 2006
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 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 · 2015
Earlier work this paper cites.
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
William Chan, Navdeep Jaitly, Quoc V. Le, and Oriol Vinyals. 2016 · 2016
Earlier work this paper cites.
Wav2letter: an end-to-end convnet-based speech recognition system
Ronan Collobert, Christian Puhrsch, and Gabriel Synnaeve. 2016 · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Speech-Transformer: A no-recurrence sequence-to-sequence model for speech recognition
Linhao Dong, Shuang Xu, and Bo Xu. 2018 · 2018
Cited alongside, same era.
Understanding back-translation at scale
Sergey Edunov, Myle Ott, Michael Auli, and David Grangier. 2018 · 2018
Cited alongside, same era.
Non-autoregressive neural machine translation
Jiatao Gu, James Bradbury, Caiming Xiong, Victor O. K. Li, and Richard Socher. 2018 · 2018
Cited alongside, same era.
Deterministic non-autoregressive neural sequence modeling by iterative refinement
Jason Lee, Elman Mansimov, and Kyunghyun Cho. 2018 · 2018
Cited alongside, same era.
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 · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Transformers without tears: Improving the normalization of self-attention
Toan Q. Nguyen and Julian Salazar. 2019 · 2019
Later among the works it cites.
SpecAugment: A simple data augmentation method for automatic speech recognition
Daniel S. Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D. Cubuk, and Quoc V. Le. 2019 · 2019
Later among the works it cites.
Self-attention networks for connectionist temporal classification in speech recognition
Julian Salazar, Katrin Kirchhoff, and Zhiheng Huang. 2019 · 2019
Later among the works it cites.
Imputer: Sequence modelling via imputation and dynamic programming
William Chan, Chitwan Saharia, Geoffrey E. Hinton, Mohammad Norouzi, and Navdeep Jaitly. 2020 · 2020
Closest in time.
ContextNet: Improving convolutional neural networks for automatic speech recognition with global context
Wei Han, Zhengdong Zhang, Yu Zhang, Jiahui Yu, Chung-Cheng Chiu, James Qin, Anmol Gulati, Ruoming Pang, and Yonghui Wu. 2020 · 2020
Closest in time.
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Mask-Predict: Parallel decoding of conditional masked language models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu, and Luke Zettlemoyer. 2019 · 2019
Cited alongside, same era.
A comparative study on transformer vs RNN in speech applications
Shigeki Karita, Xiaofei Wang, Shinji Watanabe, Takenori Yoshimura, Wangyou Zhang, Nanxin Chen, Tomoki Hayashi, Takaaki Hori, Hirofumi Inaguma, Ziyan Jiang, Masao Someki, Nelson Enrique Yalta Soplin, and Ryuichi Yamamoto. 2019 · 2019
Cited alongside, same era.
Mask CTC: Non-autoregressive end-to-end ASR with CTC and mask predict
Yosuke Higuchi, Shinji Watanabe, Nanxin Chen, Tetsuji Ogawa, and Tetsunori Kobayashi. 2020 · 2020
Closest in time.
QuartzNet: Deep automatic speech recognition with 1d time-channel separable convolutions
Samuel Kriman, Stanislav Beliaev, Boris Ginsburg, Jocelyn Huang, Oleksii Kuchaiev, Vitaly Lavrukhin, Ryan Leary, Jason Li, and Yang Zhang. 2020 · 2020
Closest in time.
Masked language model scoring
Julian Salazar, Davis Liang, Toan Q. Nguyen, and Katrin Kirchhoff. 2020 · 2020
Closest in time.