The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The segmental K-means algorithm for estimating parameters of hidden Markov models
Abstract
The authors discuss and document a parameter estimation algorithm for data sequence modeling involving hidden Markov models. The algorithm, called the segmental K-means method, uses the state-optimized joint likelihood for the observation data and the underlying Markovian state sequence as the objective function for estimation. The authors prove the convergence of the algorithm and compare it with the traditional Baum-Welch reestimation method. They also print out the increased flexibility this algorithm offers in the general speech modeling framework.>
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Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
(1967) · Cited by 23,719
Forney, G. D. (1973) · Proceedings of the IEEE · doi:10.1109/proc.1973.9030 · Cited by 5,647
An introduction to hidden Markov models
Rabiner, L., & Juang, B. (1986) · IEEE ASSP Magazine · doi:10.1109/massp.1986.1165342 · Cited by 4,775
Self-citationMaximum Likelihood from Incomplete Data via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1976) · Cited by 4,517
Baum, L. E., Petrie, T., Soules, G., & Weiss, N. (1970) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177697196 · Cited by 4,297
A Maximum Likelihood Approach to Continuous Speech Recognition
Bahl, L. R., Jelinek, F., & Mercer, R. L. (1983) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1983.4767370 · Cited by 1,212
Nonlinear Programming: A Unified Approach.
Beale, E. M. L., & Zangwill, W. (1970) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2343701 · Cited by 1,057
Nonlinear Programming: A Unified Approach
Peterson, D. W., & Zangwill, W. I. (1972) · Econometrica · doi:10.2307/1909424 · Cited by 1,005
Levinson, S. E., Rabiner, L. R., & Sondhi, M. M. (1983) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1983.tb03114.x · Cited by 978
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Cited by
Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains
Gauvain, J.-L., & Lee, C.-H. (1994) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.279278 · Cited by 2,108
Joint data and channel estimation using blind trellis search techniques
Seshadri, N. (1994) · IEEE Transactions on Communications · doi:10.1109/tcomm.1994.580208 · Cited by 257
Metadata
- Authors
- Juang, B.-H., & Rabiner, L. R.
- Venue
- IEEE Transactions on Acoustics, Speech, and Signal Processing
- Published
- 1990
- Volume
- 38
- Issue
- 9
- Pages
- 1639-1641
- ISSN
- 0096-3518 (ISSN-L)
- OpenAlex
- W2161562001
- Cited by
- 409
- References
- 18
- FWCI
- 6.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Juang, B.-H., & Rabiner, L. R. (1990). The segmental K-means algorithm for estimating parameters of hidden Markov models. IEEE Transactions on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/29.60082
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