Highway Long Short-Term Memory RNNs for Distant Speech Recognition

R. Williams and J. Peng, “An efficient gradient-based algorithm for online training of recurrent network trajectories,” Neural Computation , vol. 2, p. 490–501, 1990

1990

Earlier work this paper cites.

S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural Computation , vol. 9, no. 8, p. 1735–1438, 1997

1997

Earlier work this paper cites.

J. Fiscus, J. Ajot, N. Radde, and C. Laprun, “Multiple dimension levenshtein edit distance calculations for evaluating asr systems during simultaneous speech,” in LREC , 2006

2006

Earlier work this paper cites.

J. Carletta, ““unleashing the killer corpus: experiences in creating the multi-everything ami meeting corpus,” Language Resources & Evaluation Journal , vol. 41, no. 2, pp. 181–190, 2007

2007

Earlier work this paper cites.

F. Seide, G. Li, and D. Yu, “Conversational speech transcription using context-dependent deep neural networks,” in Proc. Annual Conference of International Speech Communication Association (INTERSPEECH) , 2011, pp. 437–440

2011

Earlier work this paper cites.

A. Stolcke, “Making the most from multiple microphones in meeting recognition,” in ICASSP , 2011

2011

Earlier work this paper cites.

D. Povey, A. Ghoshal, G. Boulianne, L. Burget, O. Glembek, N. Goel, M. Hannemann, P. Motlíček, Y. Qian, P. Schwarz, J. Silovský, G. Stemmer, and K. Veselý, “The Kaldi speech recognition toolkit,” in ASRU , 2011

2011

Earlier work this paper cites.

F. Seide, G. Li, X. Chen, and D. Yu, “Feature engineering in context-dependent deep neural networks for conversational speech transcription,” in Proc. IEEE Workshop on Automfatic Speech Recognition and Understanding (ASRU) , 2011, pp. 24–29

2011

Earlier work this paper cites.

G. E. Dahl, D. Yu, L. Deng, and A. Acero, “Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition,” IEEE Transactions on Audio, Speech and Language Processing , vol. 20, no. 1, pp. 30–42, 2012

2012

Earlier work this paper cites.

G. Hinton, L. Deng, D. Yu, G. Dahl, A. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. Sainath, and B. Kingsbury, “Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,” IEEE Signal Processing Magazine , no. 6, pp. 82–97, 2012

2012

Cited alongside, same era.

K. Kumatani, J. W. McDonough, and B. Raj, “Microphone array processing for distant speech recognition: From close-talking microphones to far-field sensors.” IEEE Signal Process. Mag. , vol. 29, no. 6, pp. 127–140, 2012

2012

Cited alongside, same era.

T. Hain, L. Burget, J. Dines, P. N. Garner, F. Grézl, A. E. Hannani, M. Huijbregts, M. Karafiát, M. Lincoln, and V. Wan, “Transcribing meetings with the amida systems.” IEEE Transactions on Audio, Speech & Language Processing , vol. 20, no. 2, pp. 486–498, 2012

2012

Cited alongside, same era.

G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Improving neural networks by preventing co-adaptation of feature detectors,” 2012. [Online]. Available: http://arxiv.org/abs/1207.0580

H. Sak, A. Senior, and F. Beaufays, “Long short-term memory recurrent neural network architectures for large scale acoustic modeling,” in Fifteenth Annual Conference of the International Speech Communication Association , 2014

2014

Later among the works it cites.

P. Swietojanski, A. Ghoshal, and S. Renals, “Convolutional neural networks for distant speech recognition,” IEEE Singal Processing Letters , vol. 21, no. 9, pp. 1120–1124, 2014

2014

Later among the works it cites.

D. Yu, A. Eversole, M. Seltzer, K. Yao, B. Guenter, O. Kuchaiev, Y. Zhang, F. Seide, G. Chen, H. Wang, J. Droppo, A. Agarwal, C. Basoglu, M. Padmilac, A. Kamenev, V. Ivanov, S. Cyphers, H. Parthasarathi, B. Mitra, Z. Huang, G. Zweig, C. Rossbach, J. Currey, J. Gao, A. May, B. Peng, A. Stolcke, M. Slaney, and X. Huang, “An introduction to computational networks and the computational network toolkit,” Microsoft Technical Report , 2014

2014

Later among the works it cites.

G. Heigold, E. McDermott, V. Vanhoucke, A. Senior, and M. Bacchiani, “Asynchronous stochastic optimization for sequence training of deep neural networks,” in ICASSP , 2014