JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Speedup of EM Algorithm by Binning Data for Normal Mixtures
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Speedup of EM Algorithm by Binning Data for Normal Mixtures
Oh, Chang-Hyuck;
  PDF(new window)
 Abstract
For a large data set the high computational cost of estimating the parameters of normal mixtures with the conventional EM algorithm is crucially impedimental in applying the algorithm to the areas requiring high speed computation such as real-time speech recognition. Simulations show that the binned EM algorithm, being compared to the standard one, significantly reduces the cost of computation without loss in accuracy of the final estimates.
 Keywords
Binned EM algorithm;execution time;normal mixtures;simulation;
 Language
Korean
 Cited by
 References
1.
Cadez, I. V., McLachlan, G. J. and McLaren, C. E. (2002). Maximum likelihood estimation of mixture densities for binned and truncated multivariate data. Machine Learning, 47, 7-34 crossref(new window)

2.
Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Ser. B, 39, 1-38

3.
Fu, Z., Yang, J., Hu, W. and Tan, T. (2004). Mixture clustering using multidi- mensional histogram for skin detection. In Proceedings of the 17th International Conference on Pattern Recognition, 4, 549-552

4.
McLachlan, G. J. and Jones, P. N. (1988). Fitting mixture models to grouped and truncated data via the EM algorithm. Biometrics, 44, 571-578 crossref(new window)

5.
McLachlan, G. J. and Krishnan, T. (1997). The EM Algorithm and Extensions. John Wiley & Sons, New York

6.
Rabiner, L. and Juang, B. (1993). Fundamentals of Speech Recognition, Prentice Hall, New Jersey

7.
Same, A., Ambroise, C. and Govaert, G. (2006). A classification EM algorithm for binned data. Computational Statistics & Data Analysis, 51, 466-480 crossref(new window)

8.
Stuttle, M. N. and Gales, M. J. F. (2001). A mixture of Gaussians front end for speech recognition. In Proceedings Eurospeech 2001

9.
Zolfaghari, P. and Robinson, T. (1996). Formant analysis using mixtures of Gaussians. In Proceedings ICSLP 96: Fourth International Conference on Spoken Language Processing

10.
Zolfaghari, P. and Robinson, T. (1997). A segmental formant vocoder based on linearly varying mixture of Gaussians. In Proceedings Eurospeech '97