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Connectionist Temporal Classification (CTC) based end-to-end speech recognition system usually need to incorporate an external language model by using WFST-based decoding in order to achieve promising results.
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2004
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L. Zhou, Y. Shi, J. Feng, and A. Sears, “Data mining for detecting errors in dictation speech recognition,”
2005
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A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, “Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks,” in
2006
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A. Graves and N. Jaitly, “Towards end-to-end speech recognition with recurrent neural networks,” in
2014
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2014
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2014
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2014
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J. K. Chorowski, D. Bahdanau, D. Serdyuk, K. Cho, and Y. Bengio, “Attention-based models for speech recognition,” in
2015
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Y. Miao, M. Gowayyed, and F. Metze, “EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding,” in
2015
Cited alongside, same era.
J. Li, H. Zhang, X. Cai, and B. Xu, “Towards end-to-end speech recognition for chinese mandarin using long short-term memory recurrent neural networks,” in
2015
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2015
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H. Sak, F. de Chaumont Quitry, T. Sainath, K. Rao
2015
Cited alongside, same era.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in
2017
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2017
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G. Klein, Y. Kim, Y. Deng, J. Senellart, and A. M. Rush, “OpenNMT: Open-source toolkit for neural machine translation,” in
2017
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C.-C. Chiu, T. N. Sainath, Y. Wu, R. Prabhavalkar, P. Nguyen, Z. Chen, A. Kannan, R. J. Weiss, K. Rao, E. Gonina
2018
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A. Kannan, Y. Wu, P. Nguyen, T. N. Sainath, Z. Chen, and R. Prabhavalkar, “An analysis of incorporating an external language model into a sequence-to-sequence model,” in
2018
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W. Chan, N. Jaitly, Q. Le, and O. Vinyals, “Listen, attend and spell: A neural network for large vocabulary conversational speech recognition,” in
2016
Cited alongside, same era.
D. Amodei, S. Ananthanarayanan, R. Anubhai, J. Bai, E. Battenberg, C. Case, J. Casper, B. Catanzaro, Q. Cheng, G. Chen
2016
Cited alongside, same era.
D. Bahdanau, J. Chorowski, D. Serdyuk, P. Brakel, and Y. Bengio, “End-to-end attention-based large vocabulary speech recognition,” in
2016
Cited alongside, same era.
X. Liu, X. Chen, Y. Wang, M. J. Gales, and P. C. Woodland, “Two efficient lattice rescoring methods using recurrent neural network language models,”
2016
Cited alongside, same era.
I. Loshchilov and F. Hutter, “SGDR: Stochastic gradient descent with warm restarts,”
2016
Cited alongside, same era.
S. Kim, T. Hori, and S. Watanabe, “Joint CTC-attention based end-to-end speech recognition using multi-task learning,” in
2017
Cited alongside, same era.
Later among the works it cites.
R. Errattahi, A. El Hannani, and H. Ouahmane, “Automatic speech recognition errors detection and correction: A review,”
2018
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S. Zhang, M. Lei, Z. Yan, and L. Dai, “Deep-FSMN for large vocabulary continuous speech recognition,” in
2018
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S. Zhang and M. Lei, “Acoustic modeling with DFSMN-CTC and joint CTC-CE learning,”
2018
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S. Zhang, M. Lei, Y. Liu, and W. Li, “Investigation of modeling units for mandarin speech recognition using DFSMN-CTC-SMBR,” in
2019
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