Reduced n-gram models for English and Chinese corpora
by
Le Q Ha
,
P Hanna
,
D W Stewart
,
F J Smith
BibTeX
@MISC{Ha_reducedn-gram,
author = {Le Q Ha and P Hanna and D W Stewart and F J Smith},
title = {Reduced n-gram models for English and Chinese corpora},
year = {}
}
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Abstract
Statistical language models should improve as the size of the n-grams increases from 3 to 5 or higher. However, the number of parameters and calculations, and the storage requirement increase very rapidly if we attempt to store all possible combinations of n-grams. To avoid these problems, the reduced n-grams ’ approach previously developed by O’Boyle (1993) can be applied. A reduced n-gram language model can store an entire corpus’s phrase-history length within feasible storage limits. Another theoretical
