Refinement of a Structured Language Model
<|reference_start|>Refinement of a Structured Language Model: A new language model for speech recognition inspired by linguistic analysis is presented. The model develops hidden hierarchical structure incrementally and uses it to extract meaningful information from the word history - thus enabling the use of extended distance dependencies - in an attempt to complement the locality of currently used n-gram Markov models. The model, its probabilistic parametrization, a reestimation algorithm for the model parameters and a set of experiments meant to evaluate its potential for speech recognition are presented.<|reference_end|>
@article{chelba2000refinement,
    title={Refinement of a Structured Language Model},
    author={Ciprian Chelba, Frederick Jelinek (CLSP The Johns Hopkins University)},
    journal={Proceedings of the International Conference on Advances in Pattern
  Recognition, 1998, pp. 275-284, Plymouth, UK},
    year={2000},
    archivePrefix={arXiv},
    eprint={cs/0001021},
    primaryClass={cs.CL}
}