1 |
Y. Tohkura, 'A weighted cepstral distance measure for speech recognition,' IEEE Trans. on Acoust. Speech and Signal Process., 35 (10), 1414-1422, Oct. 1987
DOI
|
2 |
김우일, 고한석, '시변 잡음에 대처하기 위한 다중 모델을 이용한 PCMM기반 특징 보상 기법,' 한국음향학회지, 23 (6), 473-480, Aug., 2004
|
3 |
H. A. David, Order statistics, (John Wiley & Sons, NY, 1981)
|
4 |
A. Acero, Acoustical and environmental robustness in automatic speech recognition, (Kluwer Academic Polishers, Boston, MA, 1993)
|
5 |
J. C. Junqua and J. P. Haton, Robustness in Automatic Speech Recognition, (Kluwer Academic Publishers, 1996)
|
6 |
O. Viikki, D. Bye, and K. Laurila, 'A recursive feature vector normalization approach for robust speech recognition in noise,' in Proc. ICASSP, 733-736, 1998
|
7 |
M. R. Schroeder, 'Direct (nonrecursive) relations between cepstrum and predictor coefficients,' IEEE Trans. on Acoust. Speech and Signal Process., 29 (2), 297-301, Apr. 1981
DOI
|
8 |
P. J. Moreno, B. Raj, E. Gouvea, and R. M. Stern, 'Multivariate-Gaussian-based cepstral normalization for robust speech recognition,' in Proc. ICASSP, 137-140, May 1995
|
9 |
F. N. David and N. L. Johnson, 'Statistical treatment of censored data, Part I. fundamental formulae,' Biometrika, 41, 228-240, 1956
|
10 |
M. J. F. Gales and S. J. Young, 'Robust continuous speech recognition using parallel model combination,' IEEE Trans. on Speech and Audio Process., 4 (5), 352-259, Sep. 1996
DOI
ScienceOn
|
11 |
S. A. Kassam, Signal detection in non-Gaussian noise, (Springer-Verlag, NY, 1988)
|
12 |
J. C. Junqua and H. Wakita, 'A comparative study of cepstral lifters and distance measures for all pole models of speech in noise,' in Proc. of ICASSP, 476-479, May 1989
|