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This paper presents a simple end-to-end model for speech recognition, combining a convolutional network based acoustic model and a graph decoding.
Maximum mutual information estimation of hidden markov model parameters for speech recognition
Bahl, L. R., Brown, P. F., de Souza, P. V., and Mercer, R. L · 1986
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Bottou, L · 1991
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Hypothesis spaces for minimum bayes risk training in large vocabulary speech recognition
Gibson, M., and Hain, T · 2006
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Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
Graves, A., Fernández, S., Gomez, F., and Schmidhuber, J · 2006
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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
Hinton, G., Deng, L., Yu, D., Dahl, G. E., Mohamed, A.-r., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T. N., et al · 2012
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Acoustic modeling using deep belief networks
Mohamed, A.-r., Dahl, G. E., and Hinton, G · 2012
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Speech recognition with deep recurrent neural networks
Graves, A., Mohamed, A.-r., and Hinton, G · 2013
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Scalable modified kneser-ney language model estimation
Heafield, K., Pouzyrevsky, I., Clark, J. H., and Koehn, P · 2013
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Palaz, D., Collobert, R., and Doss, M. M · 2013
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Joint training of convolutional and non-convolutional neural networks
Soltau, H., Saon, G., and Sainath, T. N · 2014
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Deep speech 2: End-to-end speech recognition in english and mandarin
Amodei, D., Anubhai, R., Battenberg, E., Case, C., Casper, J., Catanzaro, B., Chen, J., Chrzanowski, M., Coates, A., Diamos, G., et al · 2015
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Eesen: End-to-end speech recognition using deep rnn models and wfst-based decoding
Miao, Y., Gowayyed, M., and Metze, F · 2015
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Analysis of cnn-based speech recognition system using raw speech as input
Palaz, D., Collobert, R., et al · 2015
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Librispeech: an asr corpus based on public domain audio books
Panayotov, V., Chen, G., Povey, D., and Khudanpur, S · 2015
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Speaker adaptation of neural network acoustic models using i-vectors
Saon, G., Soltau, H., Nahamoo, D., and Picheny, M · 2013
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Deep speech: Scaling up end-to-end speech recognition
Hannun, A., Case, C., Casper, J., Catanzaro, B., Diamos, G., Elsen, E., Prenger, R., Satheesh, S., Sengupta, S., Coates, A., et al · 2014
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Joint phoneme segmentation inference and classification using crfs
Palaz, D., Magimai-Doss, M., and Collobert, R · 2014
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Gmm-free dnn training
Senior, A., Heigold, G., Bacchiani, M., and Liao, H · 2014
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Jhu aspire system: Robust lvcsr with tdnns, i-vector adaptation, and rnn-lms
Peddinti, V., Chen, G., Manohar, V., Ko, T., Povey, D., and Khudanpur, S · 2015
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A time delay neural network architecture for efficient modeling of long temporal contexts
Peddinti, V., Povey, D., and Khudanpur, S · 2015
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The ibm 2015 english conversational telephone speech recognition system
Saon, G., Kuo, H.-K. J., Rennie, S., and Picheny, M · 2015
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Very deep multilingual convolutional neural networks for lvcsr
Sercu, T., Puhrsch, C., Kingsbury, B., and LeCun, Y · 2015
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