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End-to-end architectures have been recently proposed for spoken language understanding (SLU) and semantic parsing.
Spoken Dialogues with Computers
Renato De Mori, · 1997
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“Long short-term memory,”
S. Hochreiter and J. Schmidhuber, · 1997
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“Semantic annotation of the french media dialog corpus,”
H. Bonneau-Maynard, S. Rosset, C. Ayache, A. Kuhn, and D. Mostefa, · 2005
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“Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,”
A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, · 2006
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“Concept segmentation and labeling for conversational speech,”
M. Dinarelli, A. Moschitti, and G. Riccardi, · 2009
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“Comparing stochastic approaches to spoken language understanding in multiple languages,”
S. Hahn, M. Dinarelli, C. Raymond, F. Lefèvre, P. Lehen, R. De Mori, A. Moschitti, H. Ney, and G. Riccardi, · 2010
Earlier work this paper cites.
“Sequence to sequence learning with neural networks,”
I. Sutskever, O. Vinyals, and Q. V. Le, · 2014
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“Neural machine translation by jointly learning to align and translate,”
D. Bahdanau, K. Cho, and Y. Bengio, · 2014
Earlier work this paper cites.
“Dropout: A simple way to prevent neural networks from overfitting,”
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, · 2014
Cited alongside, same era.
“Deep speech 2: End-to-end speech recognition in english and mandarin,”
D. Amodei, R. Anubhai, E. Battenberg, C. Case, J. Casper, B. Catanzaro, J. Chen, M. Chrzanowski, A. Coates, G. Diamos, E. Elsen, J. H. Engel, L. Fan, C. Fougner, T. Han, A. Y. Hannun, B. Jun, P. LeGresley, L. Lin, S. Narang, A. Y. Ng, S. Ozair, R. Prenger, J. Raiman, S. Satheesh, D. Seetapun, S. Sengupta, Y. Wang, Z. Wang, C. Wang, B. Xiao, D. Yogatama, J. Zhan, and Z. Zhu, · 2015
Cited alongside, same era.
“Scheduled sampling for sequence prediction with recurrent neural networks,”
S. Bengio, O. Vinyals, N. Jaitly, and N. Shazeer, · 2015
Cited alongside, same era.
“Inferring algorithmic patterns with stack-augmented recurrent nets,”
A. Joulin and T. Mikolov, · 2015
Cited alongside, same era.
“Attention is all you need,”
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, L. Kaiser, and I. Polosukhin, · 2017
Later among the works it cites.
“Towards end-to-end spoken language understanding,”
D. Serdyuk, Y. Wang, C. Fuegen, A. Kumar, B. Liu, and Y. Bengio, · 2018
Later among the works it cites.
“End-to-end named entity and semantic concept extraction from speech,”
S. Ghannay, A. Caubrière, Y. Estève, N. Camelin, E. Simonnet, A. Laurent, and E. Morin, · 2018
Later among the works it cites.
“On the practical computational power of finite precision rnns for language recognition,”
G. Weiss, Y. Goldberg, and E. Yahav, · 2018
Later among the works it cites.
“From audio to semantics: Approaches to end-to-end spoken language understanding,”
P. Haghani, A. Narayanan, M. Bacchiani, G. Chuang, N. Gaur, P. Moreno, R. Prabhavalkar, Z. Qu, and A. Waters, · 2018
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D. P. Kingma and J. Ba, · 2015
Cited alongside, same era.
“Listen and translate: A proof of concept for end-to-end speech-to-text translation,”
A. Berard, O. Pietquin, C. Servan, and L. Besacier, · 2016
Cited alongside, same era.
“Sequence-to-sequence models can directly transcribe foreign speech,”
R. J. Weiss, J. Chorowski, N. Jaitly, Y. Wu, and Z. Chen, · 2017
Cited alongside, same era.
“ASR error management for improving spoken language understanding,”
E. Simonnet, S. Ghannay, N. Camelin, Y. Estève, and R. De Mori, · 2017
Cited alongside, same era.
Later among the works it cites.
A. Caubrière, N. A. Tomashenko, A. Laurent, E. Morin, N. Camelin, and Y. Estève, · 2019
Later among the works it cites.
“Speech model pre-training for end-to-end spoken language understanding,”
L. Lugosch, M. Ravanelli, P. Ignoto, V. S. Tomar, and Y. Bengio, · 2019
Later among the works it cites.
“Hybrid neural models for sequence modelling: The best of three worlds,”
M. Dinarelli and L. Grobol, · 2019
Later among the works it cites.