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We study the segmental recurrent neural network for end-to-end acoustic modelling.
Y. He and E. Fosler-Lussier, “Efficient segmental conditional random fields for phone recognition,” in
1901
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G. Zweig, “Classification and recognition with direct segment models,” in
2012
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E. Fosler-Lussier, Y. He, P. Jyothi, and R. Prabhavalkar, “Conditional random fields in speech, audio, and language processing,”
2013
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O. Abdel-Hamid, L. Deng, D. Yu, and H. Jiang, “Deep segmental neural networks for speech recognition.” in
2013
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2013
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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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A. Hannun, C. Case, J. Casper, B. Catanzaro, G. Diamos, E. Elsen, R. Prenger
2014
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2014
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W. Zaremba, I. Sutskever, and O. Vinyals, “Recurrent neural network regularization,”
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2015
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L. Kong, C. Dyer, and N. A. Smith, “Segmental recurrent neural networks,”
2015
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Y. He and E. Fosler-Lussier, “Segmental conditional random fields with deep neural networks as acoustic models for first-pass word recognition,” in
2015
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H. Tang, W. Wang, K. Gimpel, and K. Livescu, “Discriminative segmental cascades for feature-rich phone recognition,” in
2015
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