Spoken language understanding using the Hidden Vector State Model

@article{He2006SpokenLU,
  title={Spoken language understanding using the Hidden Vector State Model},
  author={Yulan He and Steve J. Young},
  journal={Speech Communication},
  year={2006},
  volume={48},
  pages={262-275}
}
Abstract The Hidden Vector State (HVS) Model is an extension of the basic discrete Markov model in which context is encoded as a stack-oriented state vector. State transitions are factored into a stack shift operation similar to those of a push-down automaton followed by the push of a new preterminal category label. When used as a semantic parser, the model can capture hierarchical structure without the use of treebank data for training and it can be trained automatically using expectation… CONTINUE READING
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