Regularized subspace gaussian mixture models for speech recognition

IEEE Signal Processing Letters

Volumn 18, Issue 7, 2011, Pages 419-422

  Lu, Liang ^a   Ghoshal, Arnab ^b   Renals, Steve ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b SAARLAND UNIVERSITY   (Germany)

Author keywords

ellel2 norm penalty; elastic net; regularization; sparsity; subspace Gaussian mixture models

Indexed keywords

ELLEL2-NORM PENALTY; ELASTIC NET; GAUSSIAN MIXTURE MODEL; REGULARIZATION; SPARSITY;

GAUSSIAN DISTRIBUTION; MAXIMUM LIKELIHOOD ESTIMATION;

SPEECH RECOGNITION;

EID: 79958067294     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2011.2157820     Document Type: Article

References (15)

1. G. Sivaram, S. Nemala, M. Elhilali, T. Tran, and H. Hermansky, "Sparse coding for speech recognition," in Proc. ICASSP, 2010, pp. 4346-4349.
2. T. Sainath, A. Carmi, D. Kanevsky, and B. Ramabhadran, "Bayesian compressive sensing for phonetic classification," in Proc. ICASSP, 2010, pp. 4370-4373.
3. T. Sainath, B. Ramabhadran, D. Nahamoo, D. Kanevsky, and A. Sethy, "Sparse representation features for speech recognition," in Proc. IN-TERSPEECH, 2010, pp. 2254-2257.
4. M. K. Omar, "Regularized feature-based maximum likelihood linear regression for speech recognition," Proc. INTERSPEECH, pp. 1561-1564, 2007.
5. D. Povey et al., "Subspace Gaussian mixture models for speech recognition," in Proc. ICASSP, 2010, pp. 4330-4333.
6. D. Povey and L. Burget, "Subspace Gaussian mixture models-A structured model for speech recognition," Comput. Speech Lang., vol. 25, no. 2, pp. 404-439, Apr. 2011.
7. P. Kenny, "Joint Factor Analysis of Speaker and Session Variability: Theory and Algorithms," Centre de recherche informatique de Montreal, Montreal, QC, Canada, 2005, Tech. Rep. CRIM-06/08-13.
8. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference and Prediction. Berlin, Germany: Springer, 2005.
9. H. Zou and T. Hastie, "Regularization and variable selection via the elastic net," J. Royal Statist. Soc. B (Statist. Methodol.), vol. 67, no. 2, pp. 301-320, 2005. (Pubitemid 40465877)
10. D. Povey, "A Tutorial-Style Introduction to Subspace Gaussian Mixture Models for Speech Recognition," Microsoft Research, Redmond, WA, 2009, Tech. Rep. MSR-TR-2009-111, .
11. X. Zhao, Y. Dong, J. Zhao, L. Lu, J. Liu, and H. Wang, "Variational Bayesian joint factor analysis for speaker verification," in Proc. ICASSP, 2009, pp. 4049-4052.
12. R. Tibshirani, "Regression shrinkage and selection via the lasso," J. Royal Statist. Soc. B (Statist. Methodol.), vol. 58, no. 1, pp. 267-288, 1996.
13. M. Figueiredo, R. Nowak, and S. Wright, "Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems," IEEE J. Sel. Topics Signal Process., vol. 1, no. 4, pp. 586-597, 2007. (Pubitemid 351276802)
14. P. Woodland, J. Odell, V. Valtchev, and S. Young, "Large vocabulary continuous speech recognition using HTK," in Proc. ICASSP, 1994, pp. 125-128.
15. S. Young et al., The HTK Book. Cambridge, U.K.: Cambridge Univ. Press, 2002.