Training Hidden Markov Models with Multiple Observations-A Combinatorial Method

@article{Li2000TrainingHM,
  title={Training Hidden Markov Models with Multiple Observations-A Combinatorial Method},
  author={Xiaolin Li and Marc Parizeau and R{\'e}jean Plamondon},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
  year={2000},
  volume={22},
  pages={371-377}
}
Hidden Markov models (HMM) are stochastic models capable of statistical learning and classification. They have been applied in speech recognition and handwriting recognition because of their great adaptability and versatility in handling sequential signals. On the other hand, as these models have a complex structure and also because the involved data sets usually contain uncertainty, it is difficult to analyze the multiple observation training problem without certain assumptions. For many years… 

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