A structured language model

Authors:
Ciprian Chelba
Affiliations:
The Johns Hopkins University, CLSP, Baltimore, MD
Venue:
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Year:
1997

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Abstract

The paper presents a language model that develops syntatic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. The model assigns probability to every joint sequence of words-binary-parse-structure with headword annotation. The model, its probabilistic parametrization, and a set of experiments meant to evaluate its predictive power are presented.