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ML estimation of a stochastic linear system with the EM algorithm and its application to speech recognition
Abstract
A nontraditional approach to the problem of estimating the parameters of a stochastic linear system is presented. The method is based on the expectation-maximization algorithm and can be considered as the continuous analog of the Baum-Welch estimation algorithm for hidden Markov models. The algorithm is used for training the parameters of a dynamical system model that is proposed for better representing the spectral dynamics of speech for recognition. It is assumed that the observed feature vectors of a phone segment are the output of a stochastic linear dynamical system, and it is shown how the evolution of the dynamics as a function of the segment length can be modeled using alternative assumptions. A phoneme classification task using the TIMIT database demonstrates that the approach is the first effective use of an explicit model for statistical dependence between frames of speech.>
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Cites
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Cited by
From HMM's to segment models: a unified view of stochastic modeling for speech recognition
Ostendorf, M., Digalakis, V. V., & Kimball, O. A. (1996) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.536930 · Cited by 587
Self-citationLearning dynamic Bayesian networks
Ghahramani, Z. (1998) · Lecture Notes in Computer Science · doi:10.1007/bfb0053999 · Cited by 543
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
Chan, A. B., & Vasconcelos, N. (2008) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.70738 · Cited by 459
Estimating common trends in multivariate time series using dynamic factor analysis
Zuur, A. F., Fryer, R. J., Jolliffe, I. T., Dekker, R., & Beukema, J. J. (2003) · Environmetrics · doi:10.1002/env.611 · Cited by 311
Kang, J., Wang, L., Yan, C., Wang, J., Liang, X., & He, Y. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.033 · Cited by 111
Metadata
- Authors
- Digalakis, V., Rohlicek, J. R., & Ostendorf, M.
- Venue
- IEEE Transactions on Speech and Audio Processing
- Published
- 1993
- Volume
- 1
- Issue
- 4
- Pages
- 431-442
- ISSN
- 1063-6676 (ISSN-L)
- OpenAlex
- W2149361029
- Cited by
- 228
- References
- 1
- FWCI
- 4.94
- Type
- journal article
- Language
- en
- Open access
- closed
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- Digalakis, V., Rohlicek, J. R., & Ostendorf, M. (1993). ML estimation of a stochastic linear system with the EM algorithm and its application to speech recognition. IEEE Transactions on Speech and Audio Processing. https://doi.org/10.1109/89.242489
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