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29 March 2024
 
  » arxiv » cs.CL/9809026

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Prefix Probabilities from Stochastic Tree Adjoining Grammars
Mark-Jan Nederhof ; Anoop Sarkar ; Giorgio Satta ;
Date 18 Sep 1998
Journal In Proceedings of COLING-ACL ’98 (Montreal)
Subject Computation and Language ACM-class: I.2.7; D.3.1 | cs.CL
AffiliationDFKI), Anoop Sarkar (UPenn) and Giorgio Satta (UPadova
AbstractLanguage models for speech recognition typically use a probability model of the form Pr(a_n | a_1, a_2, ..., a_{n-1}). Stochastic grammars, on the other hand, are typically used to assign structure to utterances. A language model of the above form is constructed from such grammars by computing the prefix probability Sum_{w in Sigma*} Pr(a_1 ... a_n w), where w represents all possible terminations of the prefix a_1 ... a_n. The main result in this paper is an algorithm to compute such prefix probabilities given a stochastic Tree Adjoining Grammar (TAG). The algorithm achieves the required computation in O(n^6) time. The probability of subderivations that do not derive any words in the prefix, but contribute structurally to its derivation, are precomputed to achieve termination. This algorithm enables existing corpus-based estimation techniques for stochastic TAGs to be used for language modelling.
Source arXiv, cs.CL/9809026
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