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Автор MacKay, David J. C.
Автор Peto, Linda C. Bauman
Дата выпуска 1995
dc.description AbstractWe 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.
Формат application.pdf
Издатель Cambridge University Press
Копирайт Copyright © Cambridge University Press 1995
Название A hierarchical Dirichlet language model
Тип research-article
DOI 10.1017/S1351324900000218
Electronic ISSN 1469-8110
Print ISSN 1351-3249
Журнал Natural Language Engineering
Том 1
Первая страница 289
Последняя страница 308
Аффилиация MacKay David J. C.; Cavendish LaboratoryCambridge CB3 0HE, UK email: mackay@mrao.cam.ac.uk
Аффилиация Peto Linda C. Bauman; University of Toronto
Выпуск 3

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