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Refinement of a Structured Language Model

Ciprian Chelba·Frederick Jelinek
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Abstract

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.

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Ciprian Chelba, Frederick Jelinek. 2000-01-24. Refinement of a Structured Language Model. https://arxiv.org/abs/cs/0001021

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