Topology free hidden Markov models: application to background modeling
作者： B. Stenger , V. Ramesh , N. Paragios , F. Coetzee , J.M. Buhmann
关键词:
摘要: … We can do the same analysis for other model selection criteria such as the AIC criterion [A74]. The state splitting scheme using the MDL-criterion can be written therefore as follows: …
ieeecomputersociety.org
researchgate.net 参考文章(21)
V.V. Digalakis, L.G. Neumeyer, Speaker adaptation using combined transformation and Bayesian methods IEEE Transactions on Speech and Audio Processing. ,vol. 4, pp. 294- 300 ,(1996) , 10.1109/89.506933
Radford M. Neal, Geoffrey E. Hinton, A view of the EM algorithm that justifies incremental, sparse, and other variants Proceedings of the NATO Advanced Study Institute on Learning in graphical models. pp. 355- 368 ,(1998) , 10.1007/978-94-011-5014-9_12
J. Rittscher, J. Kato, S. Joga, A. Blake, A Probabilistic Background Model for Tracking european conference on computer vision. pp. 336- 350 ,(2000) , 10.1007/3-540-45053-X_22
Frederick Jelinek, Statistical methods for speech recognition ,(1997)
Steven J. Nowlan, Soft competitive adaptation: neural network learning algorithms based on fitting statistical mixtures Carnegie Mellon University. ,(1991)
Nir Friedman, Stuart Russell, Image segmentation in video sequences: a probabilistic approach uncertainty in artificial intelligence. pp. 175- 181 ,(1997)
C. Montacie, M.-J. Caratay, C. Barras, Mixture splitting technique and temporal control in a HMM-based recognition system international conference on spoken language processing. ,vol. 2, pp. 977- 980 ,(1996) , 10.1109/ICSLP.1996.607766
Jorma Rissanen, Stochastic Complexity and Modeling Annals of Statistics. ,vol. 14, pp. 1080- 1100 ,(1986) , 10.1214/AOS/1176350051
J. Takami, S. Sagayama, A successive state splitting algorithm for efficient allophone modeling international conference on acoustics, speech, and signal processing. ,vol. 1, pp. 573- 576 ,(1992) , 10.1109/ICASSP.1992.225855
M. Ostendorf, H. Singer, HMM topology design using maximum likelihood successive state splitting Computer Speech & Language. ,vol. 11, pp. 17- 41 ,(1997) , 10.1006/CSLA.1996.0021