A hierarchical Dirichlet language model
作者： David J. C. MacKay , Linda C. Bauman Peto
DOI: 10.1017/S1351324900000218
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摘要: We discuss a hierarchical probabilistic model whose predictions are similar to those of the popular language modelling procedure known as 'smoothing'. A number interesting differences from smoothing emerge. The insights gained view this problem point towards new directions for modelling. ideas paper also applicable other problems such triphomes in speech, and DNA protein sequences molecular biology. algorithm is compared with on two million word corpus. methods prove be about equally accurate, using fewer computational resources.
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