Bidirectional truncated recurrent neural networks for efficient speech denoising

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn , Issue , 2013, Pages 2973-2977

  Brakel, Philémon ^a   Stroobandt, Dirk ^a   Schrauwen, Benjamin ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Deep learning; Recurrent neural networks; Robust ASR

Indexed keywords

NETWORK ARCHITECTURE; PARALLEL ARCHITECTURES; PROGRAM PROCESSORS;

DEEP LEARNING; FEED-FORWARD ARCHITECTURES; FRONT END; NOISE CONDITIONS; PARALLEL COMPUTING ARCHITECTURE; PARALLELIZATIONS; ROBUST ASR; SPEECH DENOISING;

RECURRENT NEURAL NETWORKS;

EID: 84896502897     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. A. L. Maas, Q. V. Le, T. M. O'Neil, O. Vinyals, P. Nguyen, and A. Y. Ng, "Recurrent neural networks for noise reduction in robust asr, " in INTERSPEECH. ISCA, 2012.
2. "Advanced front-end feature extraction algorihtm, " Tech. Rep. ETSI ES 202 050, 2007.
3. M. J. F. Gales, "Model-based techniques, for noise robust speech recognition, " Ph.D. dissertation, University of Cambridge, 1995.
4. L. Deng, A. Acero, J. L. Droppo, and J. X. Huang, "Highperformance robust speech recognition using stereo training data, " in Proc. ICASSP, Salt Lake City, UT, May 2001, pp. 301-304.
5. H. Hermansky, D. P. Ellis, and S. Sharma, "Tandem connectionist feature extraction for conventional hmm systems, " in Acoustics, Speech, and Signal Processing, 2000. ICASSP'00. Proceedings. 2000 IEEE International Conference on, vol. 3. IEEE, 2000, pp. 1635-1638.
6. S. Tamura and A. Waibel, "Noise reduction using connectionist models, " in Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on. IEEE, 1988, pp. 553-556.
7. Y. Bengio, "Learning deep architectures for ai, " Foundations and Trends(R) in Machine Learning, vol. 2, no. 1, pp. 1-127, 2009.
8. G. E. Dahl, D. Yu, L. Deng, and A. Acero, "Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition, " Audio, Speech, and Language Processing, IEEE Transactions on, vol. 20, no. 1, pp. 30-42, 2012.
9. T. Robinson, M. Hochberg, and S. Renals, "Ipa: Improved phone modelling with recurrent neural networks, " in Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on, vol. 1. IEEE, 1994, pp. I-37.
10. O. Vinyals, S. Ravuri, and D. Povey, "Revisiting Recurrent Neural Networks for Robust ASR, " in ICASSP, 2012.
11. Y. Bengio, P. Simard, and P. Frasconi, "Learning long-term dependencies with gradient descent is difficult, " Neural Networks, IEEE Transactions on, vol. 5, no. 2, pp. 157-166, 1994.
12. M. J. Wainwright and M. I. Jordan, "Graphical models, exponential families, and variational inference, " Found. Trends Mach. Learn., vol. 1, no. 1-2, pp. 1-305, Jan. 2008. [Online]. Available: http://dx.doi.org/10.1561/ 2200000001.
13. M. Schuster and K. K. Paliwal, "Bidirectional recurrent neural networks, " Signal Processing, IEEE Transactions on, vol. 45, no. 11, pp. 2673-2681, 1997.
14. A. Graves and J. Schmidhuber, "Framewise phoneme classification with bidirectional lstm and other neural network architectures, " Neural Networks, vol. 18, no. 5, pp. 602-610, 2005.
15. D. Pearce, H. gnter Hirsch, and E. E. D. Gmbh, "The aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions, " in in ISCA ITRW ASR2000, 2000, pp. 29-32.
16. J. Martens, "Deep learning via hessian-free optimization, " in ICML, J. Fürnkranz and T. Joachims, Eds. Omnipress, 2010, pp. 735-742.
17. J. Martens and I. Sutskever, "Learning recurrent neural networks with hessian-free optimization, " in Proc. 28th Int. Conf. on Machine Learning, 2011.
18. J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley, and Y. Bengio, "Theano: A cpu and gpu math compiler in python, " in Proceedings of the 9th Python in Science Conference, S. van der Walt and J. Millman, Eds., 2010, pp. 3 - 10.
19. J. Droppo, L. Deng, and A. Acero, "Evaluation of splice on the aurora 2 and 3 tasks, " in International Conference on Spoken Language Processing, 2002, pp. 29-32.
20. J. F. Gemmeke and T. Virtanen, "Artificial and online acquired noise dictionaries for noise robust ASR, " in INTERSPEECH, 2010, pp. 2082-2085.