1 |
Huang, X., Acero, A., and Hon, H.-W (2001), Spoken Language Processing: A Guide to Theory, Algorithm, and System Development. Prentice Hall.
|
2 |
Gales, M. (2000), Cluster adaptive training of hidden Markov models, IEEE Trans. Speech and Audio Process., Vol. 8, No. 4.
|
3 |
Kuhn, R. et al. (1998), Eigenvoices for speaker adaptation. in Proc. ICSLP.
|
4 |
Povey, D. et al. (2010), Subspace Gaussian Mixture Models for speech recognition, in Proc. ICASSP.
|
5 |
Povey, D. et al. (2011), The subspace Gaussian mixture model -A structured model for speech recognition, Computer Speech and Language, Vol. 25, No. 2.
|
6 |
Burget, L. et al. (2010), Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models, in Proc. ICASSP.
|
7 |
Lu, L. et al. (2012), Maximum a posteriori adaptation of subspace Gaussian mixture models for cross-lingual speech recognition, in Proc. ICASSP.
|
8 |
Hamidi, S. and Rose, R. C. (2013), Phonetic subspace adaptation for automatic speech recognition, in Proc. ICASSP.
|
9 |
Kim, Y. and Kim, H. (2014), Constrained mle-based speaker adaptation with l1 regularization, in Proc. ICASSP.
|
10 |
Chen, S. S. et al. (1998), Atomic Decomposition by Basis Pursuit, SIAM J. Scientific Computing, Vol. 20.
|
11 |
Tibshirani, R. (1996), Regression Shrinkage and Selection via the Lasso, J. Roy. Stat. Soc. Series B (Methodological), Vol. 58, No. 1.
|
12 |
Povey, D. (2009), A tutorial-style introduction to subspace Gaussian mixture models for speech recognition, Microsoft research, Redmond, WA, Tech. Rep.
|
13 |
Benzeghiba, M. et al. (2007), Automatic speech recognition and speech variability: A review, Speech Comm., Vol. 49, No. 10-11.
DOI
|
14 |
Figueiredo, M. A. et al. (2007), Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems, IEEE J. Selected Topics Signal Process., Vol. 1, No. 4.
|
15 |
Olsen, P. A. et al. (2011), Sparse Maximum A Posteriori adaptation, in Proc. ASRU.
|
16 |
Lu, L. et al. (2011), Regularized subspace Gaussian mixture models for cross-lingual speech recognition, in Proc. ASRU.
|
17 |
Lu, L. et al. (2011), Regularized Subspace Gaussian Mixture Models for Speech Recognition, IEEE Signal Processing Letters, Vol. 18, No. 7.
|
18 |
Candes, E. J., Wakin, M. B., and Boyd, S. P. (2008), Enhancing sparsity by reweighted L1 minimization, J. Fourier Analysis Applicat., Vol. 14.
|
19 |
Asif, M. S. and Romberg, J. (2013), Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization, IEEE Trans. Signal Process., Vol. 61, No. 3.
|
20 |
Povey, D., Ghoshal, A., and Boulianne, G. (2011), The Kaldi speech recognition toolkit, in Proc. ASRU.
|