Refinement of a Structured Language Model

dc.creatorChelba, Ciprian
dc.creatorJelinek, Frederick
dc.date2000-01-24
dc.date.accessioned2026-07-07T03:15:51Z
dc.date.available2026-07-07T03:15:51Z
dc.descriptionA 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.
dc.description10 pages
dc.identifierhttps://arxiv.org/abs/cs/0001021
dc.identifierhttp://arxiv.org/abs/cs/0001021
dc.identifierProceedings of the International Conference on Advances in Pattern Recognition, 1998, pp. 275-284, Plymouth, UK
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30141
dc.subjectComputation and Language
dc.subjectG.3, I.2.7, I.5.1, I.5.4
dc.titleRefinement of a Structured Language Model
dc.typetext

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