Approximate N-Gram Markov Model for Natural Language Generation

Details Approximate N-Gram Markov Model for Natural Language Generation Approximate N-Gram Markov Model for Natural Language Generation

1994-08-24

arxiv.org/abs/cmp-lg/9408012v1

Computer Science

Computation and Language

to appear in proceedings of QUALICO-94, 6 pages, uuencoded compressed Postscript file; extract with Unix uudecode and uncompre

Scientific paper

This paper proposes an Approximate n-gram Markov Model for bag generation. Directed word association pairs with distances are used to approximate (n-1)-gram and n-gram training tables. This model has parameters of word association model, and merits of both word association model and Markov Model. The training knowledge for bag generation can be also applied to lexical selection in machine translation design.

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