Hidden Markov Models for Speech Recognition
Hidden Markov Models for Speech Recognition
Learning models for English speech recognition
ACSC '04 Proceedings of the 27th Australasian conference on Computer science - Volume 26
Hierarchical Gaussian process mixtures for regression
Statistics and Computing
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Curve prediction and clustering with mixtures of Gaussian process functional regression models
Statistics and Computing
Curve forecasting by functional autoregression
Journal of Multivariate Analysis
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In order to model the functional time series system, we developed a new model–Gaussian process hidden Markov model. We use the hidden Markov model to characterize the time order of system, and Gaussian process to model the function observations. We utilized this new model to consider the functional time series classification and prediction problem. The simulation results for real data demonstrate that our model is efficient.