A hierarchical Dirichlet language model. MacKay, D. J. & Peto, L. B. Natural language engineering, 1(3):289–307, September, 1995. abstract bibtex We discuss a hierarchical probabilistic model whose predictions are similar to those of the popular language modelling procedure known as `smoothing'. A number of interesting differences from smoothing emerge. The insights gained from a probabilistic view of this problem point towards new directions for language modelling. The ideas of this paper are also applicable to other problems, such as the modelling of triphomes in speech and DNA and protein sequences in molecular biology. The new algorithm is compared with smoothing on a two-million word corpus. The methods prove to be about equally accurate, with the hierarchical model using fewer computational resources.
@Article{ peto1,
author = {David J.C. MacKay and Linda Bauman Peto},
title = {A hierarchical Dirichlet language model},
journal = {Natural language engineering},
volume = {1},
number = {3},
month = {September},
year = {1995},
pages = {289--307},
abstract = {We discuss a hierarchical probabilistic model whose
predictions are similar to those of the popular language
modelling procedure known as `smoothing'. A number of
interesting differences from smoothing emerge. The insights
gained from a probabilistic view of this problem point
towards new directions for language modelling. The ideas of
this paper are also applicable to other problems, such as
the modelling of triphomes in speech and DNA and protein
sequences in molecular biology. The new algorithm is
compared with smoothing on a two-million word corpus. The
methods prove to be about equally accurate, with the
hierarchical model using fewer computational resources.}
}
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