Segmental Hidden Markov Models with Random Effects for Waveform Modeling
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[1] Mary P. Harper,et al. On the complexity of explicit duration HMM's , 1995, IEEE Trans. Speech Audio Process..
[2] D. Rubin,et al. Estimation in Covariance Components Models , 1981 .
[3] Michael C. Horsch,et al. Dynamic Bayesian networks , 1990 .
[4] A. Koski. Modelling ECG signals with hidden Markov models , 1996, Artif. Intell. Medicine.
[5] T. J. Bennett,et al. Analysis of seismic discrimination capabilities using regional data from western United States events , 1986 .
[6] Stephen J. Roberts,et al. Markov Models for Automated ECG Interval Analysis , 2003, NIPS.
[7] Nathan Intrator,et al. Classification of seismic signals by integrating ensembles of neural networks , 1998, IEEE Trans. Signal Process..
[8] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[9] Xiao-Li Meng,et al. Maximum likelihood estimation via the ECM algorithm: A general framework , 1993 .
[10] Christos Faloutsos,et al. Fast Time Sequence Indexing for Arbitrary Lp Norms , 2000, VLDB.
[11] N. Laird,et al. Maximum likelihood computations with repeated measures: application of the EM algorithm , 1987 .
[12] Yung-Hwan Oh,et al. A segmental-feature HMM for speech pattern modeling , 2000, IEEE Signal Process. Lett..
[13] Padhraic Smyth,et al. Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models , 2004, UAI 2004.
[14] Stephen E. Levinson,et al. Continuously variable duration hidden Markov models for automatic speech recognition , 1986 .
[15] D. Rubin,et al. The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence , 1994 .
[16] J. Ware,et al. Random-effects models for longitudinal data. , 1982, Biometrics.
[17] Michael I. Jordan. Learning in Graphical Models , 1999, NATO ASI Series.
[18] Biing-Hwang Juang,et al. Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.
[19] Brendan J. Frey,et al. A segment based probabilistic generative model of speech , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[20] Ada Wai-Chee Fu,et al. Efficient time series matching by wavelets , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).
[21] S. Jankowski,et al. Computer-aided morphological analysis of Holter ECG recordings based on support vector learning system , 2003, Computers in Cardiology, 2003.
[22] Padhraic Smyth,et al. Deformable Markov model templates for time-series pattern matching , 2000, KDD '00.
[23] Christos Faloutsos,et al. Efficient Similarity Search In Sequence Databases , 1993, FODO.
[24] SmythPadhraic,et al. Segmental Hidden Markov Models with Random Effects for Waveform Modeling , 2006 .
[25] Martin Russell,et al. A segmental HMM for speech pattern modelling , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[26] H. H. Bruun,et al. Hot-Wire Anemometry: Principles and Signal Analysis , 1996 .
[27] Eamonn J. Keogh,et al. Scaling up dynamic time warping for datamining applications , 2000, KDD '00.
[28] Stuart J. Russell,et al. Dynamic bayesian networks: representation, inference and learning , 2002 .
[29] R. Moore,et al. Explicit modelling of state occupancy in hidden Markov models for automatic speech recognition , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.
[30] Martin J. Russell,et al. Probabilistic-trajectory segmental HMMs , 1999, Comput. Speech Lang..
[31] Mari Ostendorf,et al. From HMM's to segment models: a unified view of stochastic modeling for speech recognition , 1996, IEEE Trans. Speech Audio Process..
[32] Mark J. F. Gales,et al. The theory of segmental hidden Markov models , 1993 .
[33] Eamonn J. Keogh,et al. A Probabilistic Approach to Fast Pattern Matching in Time Series Databases , 1997, KDD.
[34] Xiaodong Sun,et al. Speech recognition using hidden Markov models with polynomial regression functions as nonstationary states , 1994, IEEE Trans. Speech Audio Process..