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We present state-of-the-art automatic speech recognition (ASR) systems employing a standard hybrid DNN/HMM architecture compared to an attention-based encoder-decoder design for the LibriSpeech task.
R. Kneser and H. Ney, “Improved backing-off for m-gram language modeling,” in
1995
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, “Long short-term memory,”
1997
Earlier work this paper cites.
M. Gibson and T. Hain, “Hypothesis spaces for minimum bayes risk training in large vocabulary speech recognition,” in
2006
Earlier work this paper cites.
R. Schlüter, I. Bezrukov, H. Wagner, and H. Ney, “Gammatone features and feature combination for large vocabulary speech recognition,” in
2007
Earlier work this paper cites.
G. Hinton, L. Deng, D. Yu, G. Dahl, A.-r. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, B. Kingsbury
2012
Earlier work this paper cites.
M. Sundermeyer, R. Schlüter, and H. Ney, “LSTM neural networks for language modeling,” in
2012
Earlier work this paper cites.
A. Graves, N. Jaitly, and A.-r. Mohamed, “Hybrid speech recognition with deep bidirectional LSTM,” in
2013
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,”
2014
Earlier work this paper cites.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: a simple way to prevent neural networks from overfitting,”
2014
Earlier work this paper cites.
M. Sundermeyer, Z. Tüske, R. Schlüter, and H. Ney, “Lattice decoding and rescoring with long-span neural network language models,” in
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
S. Wiesler, A. Richard, P. Golik, R. Schlüter, and H. Ney, “RASR/NN: The RWTH neural network toolkit for speech recognition,” in
2014
Earlier work this paper cites.
V. Panayotov, G. Chen, D. Povey, and S. Khudanpur, “Librispeech: an asr corpus based on public domain audio books,” in
2015
Earlier work this paper cites.
T. Dozat, “Incorporating nesterov momentum into Adam,” Stanford University, Tech. Rep., 2015. [Online]. Available:
2015
Cited alongside, same era.
2015
Cited alongside, same era.
2015
Cited alongside, same era.
W. Chan, N. Jaitly, Q. V. Le, and O. Vinyals, “Listen, attend and spell: A neural network for large vocabulary conversational speech recognition,” in
2016
Cited alongside, same era.
P. Doetsch, A. Zeyer, and H. Ney, “Bidirectional decoder networks for attention-based end-to-end offline handwriting recognition,” in
N. Kanda, Y. Fujita, and K. Nagamatsu, “Lattice-free state-level minimum bayes risk training of acoustic models,” in
2018
Later among the works it cites.
A. Zeyer, K. Irie, R. Schlüter, and H. Ney, “Improved training of end-to-end attention models for speech recognition,” in
2018
Later among the works it cites.
A. Zeyer, A. Merboldt, R. Schlüter, and H. Ney, “A comprehensive analysis on attention models,” in
2018
Later among the works it cites.
S. Sabour, W. Chan, and M. Norouzi, “Optimal completion distillation for sequence learning,”
2018
Later among the works it cites.
2018
Later among the works it cites.
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2016
Cited alongside, same era.
R. Sennrich, B. Haddow, and A. Birch, “Neural machine translation of rare words with subword units,” in
2016
Cited alongside, same era.
2017
Cited alongside, same era.
A. Zeyer, P. Doetsch, P. Voigtlaender, R. Schlüter, and H. Ney, “A comprehensive study of deep bidirectional lstm rnns for acoustic modeling in speech recognition,” in
2017
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
Cited alongside, same era.
2017
Cited alongside, same era.
E. Battenberg, J. Chen, R. Child, A. Coates, Y. Gaur, Y. Li, H. Liu, S. Satheesh, A. Sriram, and Z. Zhu, “Exploring neural transducers for end-to-end speech recognition,” in
2017
Cited alongside, same era.
Ç. Gülçehre, O. Firat, K. Xu, K. Cho, L. Barrault, H.-C. Lin, F. Bougares, H. Schwenk, and Y. Bengio, “On using monolingual corpora in neural machine translation,”
2017
Cited alongside, same era.
A. Zeyer, T. Alkhouli, and H. Ney, “RETURNN as a generic flexible neural toolkit with application to translation and speech recognition,” in
2018
Later among the works it cites.
M. X. Chen, O. Firat, A. Bapna, M. Johnson, W. Macherey, G. Foster, L. Jones, M. Schuster, N. Shazeer, N. Parmar
2018
Later among the works it cites.
S. Toshniwal, A. Kannan, C.-C. Chiu, Y. Wu, T. N. Sainath, and K. Livescu, “A comparison of techniques for language model integration in encoder-decoder speech recognition,” in
2018
Later among the works it cites.
2019
Closest in time.
2019
Closest in time.
E. Beck, W. Zhou, R. Schlüter, and H. Ney, “Lstm language models for lvcsr in first-pass decoding and lattice-rescoring,”
2019
Closest in time.
K. Irie, A. Zeyer, R. Schlüter, and H. Ney, “Language modeling with deep Transformers,” in
2019
Closest in time.